Python Developer Jobs in Jordan

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <span>Please submit your CV in English and indicate your level of English proficiency.<br> Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems.<br> Participation is project-based, not permanent employment.<br> What this opportunity involves We're building a dataset to evaluate AI coding agents - how well a model handles real-world developer tasks.<br> You'll create challenging tasks and evaluation criteria within realistic simulated environments: Build realistic developer environments - a virtual company with codebase, infrastructure, and context (tickets, docs, conversations) that forms a believable development history Design tasks from intermediate states of these environments - craft the prompt, define what "solved" means, and ensure the task is solvable by an AI agent Write tests that verify agent solutions - accept all valid approaches and reject incorrect ones, neither too strict nor too lenient Iterate on tasks and tests based on QA feedback - review agent solutions, analyze failures, and refine until the evaluation is fair and robust What this is NOT Not data labeling Not prompt engineering Not writing code from scratch - the agent writes most of the code; you guide and evaluate What we look for 5+ years in software development Core stack: Python (FastAPI), JavaScript/TypeScript (React), Docker, Postgres, Kafka, Redis Experience writing tests (functional, integration) English proficiency - B2+ Why this is hard Frontier models are already good at coding.<br> Creating a task that genuinely challenges the best models is non-trivial.<br> You need to deeply understand where models fail and what scenarios reveal the difference between a good and a bad solution.<br> Tasks have many valid solutions - writing tests that accept all correct solutions and reject incorrect ones is harder than it sounds.<br> How it works Apply → Pass qualification(s) → Join a project → Complete tasks → Get paid Effort estimate Tasks for this project are estimated to take 20 hours to complete, depending on complexity.<br> This is an estimate and not a schedule requirement; you choose when and how to work.<br> Tasks must be submitted by the deadline and meet the listed acceptance criteria to be accepted.<br> Compensation Up to $50/hr equivalent , depending on level and pace.<br> Tasks are estimated at ~20 hours each; you set your own schedule.<br></span> </div>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <span>Please submit your CV in English and indicate your level of English proficiency.<br> Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems.<br> Participation is project-based, not permanent employment.<br> What this opportunity involves We're building a dataset to evaluate AI coding agents - how well a model handles real-world developer tasks.<br> You'll create challenging tasks and evaluation criteria within realistic simulated environments: Build realistic developer environments - a virtual company with codebase, infrastructure, and context (tickets, docs, conversations) that forms a believable development history Design tasks from intermediate states of these environments - craft the prompt, define what "solved" means, and ensure the task is solvable by an AI agent Write tests that verify agent solutions - accept all valid approaches and reject incorrect ones, neither too strict nor too lenient Iterate on tasks and tests based on QA feedback - review agent solutions, analyze failures, and refine until the evaluation is fair and robust What this is NOT Not data labeling Not prompt engineering Not writing code from scratch - the agent writes most of the code; you guide and evaluate What we look for 5+ years in software development Core stack: Python (FastAPI), JavaScript/TypeScript (React), Docker, Postgres, Kafka, Redis Experience writing tests (functional, integration) English proficiency - B2+ Why this is hard Frontier models are already good at coding.<br> Creating a task that genuinely challenges the best models is non-trivial.<br> You need to deeply understand where models fail and what scenarios reveal the difference between a good and a bad solution.<br> Tasks have many valid solutions - writing tests that accept all correct solutions and reject incorrect ones is harder than it sounds.<br> How it works Apply → Pass qualification(s) → Join a project → Complete tasks → Get paid Effort estimate Tasks for this project are estimated to take 20 hours to complete, depending on complexity.<br> This is an estimate and not a schedule requirement; you choose when and how to work.<br> Tasks must be submitted by the deadline and meet the listed acceptance criteria to be accepted.<br> Compensation Up to $50/hr equivalent , depending on level and pace.<br> Tasks are estimated at ~20 hours each; you set your own schedule.<br></span> </div>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <span>We're looking for an experienced Senior Data Scientist to design and deliver data-driven solutions that solve complex business problems and create measurable impact.<br> Working closely with business stakeholders, product teams, and technical experts, you'll transform business challenges into scalable analytical, machine learning, and GenAI solutions.<br> From defining use cases to deploying production-ready models, you'll play a key role in delivering innovative AI solutions that drive better decision-making and customer outcomes.<br> What You'll Do ❏ Collaborate with business stakeholders to identify and prioritize AI and analytics opportunities ❏ Translate business requirements into scalable data science and machine learning solutions ❏ Validate data availability and define analytical approaches for new use cases ❏ Build predictive models, machine learning solutions, and GenAI applications ❏ Design robust data pipelines and analytical workflows ❏ Apply data processing, feature engineering, and statistical modelling techniques ❏ Ensure solutions are scalable, production-ready, and aligned with software engineering and MLOps best practices ❏ Present analytical findings and recommendations to technical and executive stakeholders ❏ Communicate AI capabilities, feasibility, risks, and expected business value in a clear and practical way ❏ Mentor junior team members and support technical delivery across multiple initiatives You're Our Match If You Have ❏ Master's degree in Data Science, Computer Science, Artificial Intelligence, Mathematics, Software Engineering, or a related field ❏ 5+ years of hands-on experience delivering data science or machine learning solutions ❏ Strong Python programming skills and experience with modern data science libraries ❏ Experience building predictive models, machine learning solutions, and GenAI applications ❏ Strong understanding of statistics, data modelling, and feature engineering ❏ Experience designing scalable data pipelines and production-ready AI solutions ❏ Familiarity with MLOps, model deployment, and machine learning lifecycle management ❏ Excellent stakeholder management and communication skills ❏ Ability to translate complex technical concepts into business value Bonus Points If You Have Experience With ❏ Telecommunications or other customer-centric industries ❏ Large-scale customer analytics and segmentation ❏ Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) ❏ Cloud platforms such as Azure, AWS, or Google Cloud ❏ Databricks, Spark, or distributed data processing ❏ Docker, Kubernetes, or CI/CD pipelines ❏ Leading or mentoring technical teams</span> </div>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <span>Please submit your CV in English and indicate your level of English proficiency.<br> Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems.<br> Participation is project-based, not permanent employment.<br> What this opportunity involves We're building a dataset to evaluate AI coding agents - how well a model handles real-world developer tasks.<br> You'll create challenging tasks and evaluation criteria within realistic simulated environments: Build realistic developer environments - a virtual company with codebase, infrastructure, and context (tickets, docs, conversations) that forms a believable development history Design tasks from intermediate states of these environments - craft the prompt, define what "solved" means, and ensure the task is solvable by an AI agent Write tests that verify agent solutions - accept all valid approaches and reject incorrect ones, neither too strict nor too lenient Iterate on tasks and tests based on QA feedback - review agent solutions, analyze failures, and refine until the evaluation is fair and robust What this is NOT Not data labeling Not prompt engineering Not writing code from scratch - the agent writes most of the code; you guide and evaluate What we look for 5+ years in software development Core stack: Python (FastAPI), JavaScript/TypeScript (React), Docker, Postgres, Kafka, Redis Experience writing tests (functional, integration) English proficiency - B2+ Why this is hard Frontier models are already good at coding.<br> Creating a task that genuinely challenges the best models is non-trivial.<br> You need to deeply understand where models fail and what scenarios reveal the difference between a good and a bad solution.<br> Tasks have many valid solutions - writing tests that accept all correct solutions and reject incorrect ones is harder than it sounds.<br> How it works Apply → Pass qualification(s) → Join a project → Complete tasks → Get paid Effort estimate Tasks for this project are estimated to take 20 hours to complete, depending on complexity.<br> This is an estimate and not a schedule requirement; you choose when and how to work.<br> Tasks must be submitted by the deadline and meet the listed acceptance criteria to be accepted.<br> Compensation Up to $50/hr equivalent , depending on level and pace.<br> Tasks are estimated at ~20 hours each; you set your own schedule.<br></span> </div>

<p><h4>Description<\/h4>\n<p>Please submit your CV in English and indicate your level of English proficiency.<\/p>\n<p>Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment.<\/p>\n<h4>What this opportunity involves<\/h4>\n<p>We're building a dataset to evaluate AI coding agents - how well a model handles real-world developer tasks.<\/p>\n<p>You'll create challenging tasks and evaluation criteria within realistic simulated environments:<\/p>\n<ul>\n<li>Build realistic developer environments - a virtual company with codebase, infrastructure, and context (tickets, docs, conversations) that forms a believable development history<\/li>\n<li>Design tasks from intermediate states of these environments - craft the prompt, define what \"solved\" means, and ensure the task is solvable by an AI agent<\/li>\n<li>Write tests that verify agent solutions - accept all valid approaches and reject incorrect ones, neither too strict nor too lenient<\/li>\n<li>Iterate on tasks and tests based on QA feedback - review agent solutions, analyze failures, and refine until the evaluation is fair and robust<\/li>\n<\/ul>\n<h4>What this is not<\/h4>\n<ul>\n<li>Not data labeling<\/li>\n<li>Not prompt engineering<\/li>\n<li>Not writing code from scratch - the agent writes most of the code; you guide and evaluate<\/li>\n<\/ul>\n<h4>What we look for<\/h4>\n<ul>\n<li>5+ years in software development<\/li>\n<li>Core stack: Python (FastAPI), JavaScript\/TypeScript (React), Docker, Postgres, Kafka, Redis<\/li>\n<li>Experience writing tests (functional, integration)<\/li>\n<li>English proficiency - B2+<\/li>\n<\/ul>\n<h4>Why this is hard<\/h4>\n<p>Frontier models are already good at coding. Creating a task that genuinely challenges the best models is non-trivial. You need to deeply understand where models fail and what scenarios reveal the difference between a good and a bad solution. Tasks have many valid solutions - writing tests that accept all correct solutions and reject incorrect ones is harder than it sounds.<\/p>\n<h4>How it works<\/h4>\n<p>Apply ? Pass qualification(s) ? Join a project ? Complete tasks ? Get paid<\/p>\n<h4>Effort estimate<\/h4>\n<p>Tasks for this project are estimated to take 20 hours to complete, depending on complexity. This is an estimate and not a schedule requirement; you choose when and how to work. Tasks must be submitted by the deadline and meet the listed acceptance criteria to be accepted.<\/p>\n<h4>Compensation<\/h4>\n<p>Up to $50\/hr equivalent, depending on level and pace. Tasks are estimated at ~20 hours each; you set your own schedule.<\/p><\/p><p><\/p>

<p><h4>Description<\/h4>\n<p>Please submit your CV in English and indicate your level of English proficiency.<\/p>\n<p>Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment.<\/p>\n<h4>What this opportunity involves<\/h4>\n<p>We're building a dataset to evaluate AI coding agents - how well a model handles real-world developer tasks.<\/p>\n<p>You'll create challenging tasks and evaluation criteria within realistic simulated environments:<\/p>\n<ul>\n<li>Build realistic developer environments - a virtual company with codebase, infrastructure, and context (tickets, docs, conversations) that forms a believable development history<\/li>\n<li>Design tasks from intermediate states of these environments - craft the prompt, define what \"solved\" means, and ensure the task is solvable by an AI agent<\/li>\n<li>Write tests that verify agent solutions - accept all valid approaches and reject incorrect ones, neither too strict nor too lenient<\/li>\n<li>Iterate on tasks and tests based on QA feedback - review agent solutions, analyze failures, and refine until the evaluation is fair and robust<\/li>\n<\/ul>\n<h4>What this is not<\/h4>\n<ul>\n<li>Not data labeling<\/li>\n<li>Not prompt engineering<\/li>\n<li>Not writing code from scratch - the agent writes most of the code; you guide and evaluate<\/li>\n<\/ul>\n<h4>What we look for<\/h4>\n<ul>\n<li>5+ years in software development<\/li>\n<li>Core stack: Python (FastAPI), JavaScript\/TypeScript (React), Docker, Postgres, Kafka, Redis<\/li>\n<li>Experience writing tests (functional, integration)<\/li>\n<li>English proficiency - B2+<\/li>\n<\/ul>\n<h4>Why this is hard<\/h4>\n<p>Frontier models are already good at coding. Creating a task that genuinely challenges the best models is non-trivial. You need to deeply understand where models fail and what scenarios reveal the difference between a good and a bad solution. Tasks have many valid solutions - writing tests that accept all correct solutions and reject incorrect ones is harder than it sounds.<\/p>\n<h4>How it works<\/h4>\n<p>Apply ? Pass qualification(s) ? Join a project ? Complete tasks ? Get paid<\/p>\n<h4>Effort estimate<\/h4>\n<p>Tasks for this project are estimated to take 20 hours to complete, depending on complexity. This is an estimate and not a schedule requirement; you choose when and how to work. Tasks must be submitted by the deadline and meet the listed acceptance criteria to be accepted.<\/p>\n<h4>Compensation<\/h4>\n<p>Up to $50\/hr equivalent, depending on level and pace. Tasks are estimated at ~20 hours each; you set your own schedule.<\/p><\/p><p><\/p>

<p><h4>Description<\/h4>\n<p>Please submit your CV in English and indicate your level of English proficiency.<\/p>\n<p>Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment.<\/p>\n<h4>What this opportunity involves<\/h4>\n<p>We're building a dataset to evaluate AI coding agents - how well a model handles real-world developer tasks.<\/p>\n<p>You'll create challenging tasks and evaluation criteria within realistic simulated environments:<\/p>\n<ul>\n <li>Build realistic developer environments - a virtual company with codebase, infrastructure, and context (tickets, docs, conversations) that forms a believable development history<\/li>\n <li>Design tasks from intermediate states of these environments - craft the prompt, define what \"solved\" means, and ensure the task is solvable by an AI agent<\/li>\n <li>Write tests that verify agent solutions - accept all valid approaches and reject incorrect ones, neither too strict nor too lenient<\/li>\n <li>Iterate on tasks and tests based on QA feedback - review agent solutions, analyze failures, and refine until the evaluation is fair and robust<\/li>\n<\/ul>\n<h4>What this is not<\/h4>\n<ul>\n <li>Not data labeling<\/li>\n <li>Not prompt engineering<\/li>\n <li>Not writing code from scratch - the agent writes most of the code; you guide and evaluate<\/li>\n<\/ul>\n<h4>What we look for<\/h4>\n<ul>\n <li>5+ years in software development<\/li>\n <li>Core stack: Python (FastAPI), JavaScript\/TypeScript (React), Docker, Postgres, Kafka, Redis<\/li>\n <li>Experience writing tests (functional, integration)<\/li>\n <li>English proficiency - B2+<\/li>\n<\/ul>\n<h4>Why this is hard<\/h4>\n<p>Frontier models are already good at coding. Creating a task that genuinely challenges the best models is non-trivial. You need to deeply understand where models fail and what scenarios reveal the difference between a good and a bad solution. Tasks have many valid solutions - writing tests that accept all correct solutions and reject incorrect ones is harder than it sounds.<\/p>\n<h4>How it works<\/h4>\n<p>Apply? Pass qualification(s)? Join a project? Complete tasks? Get paid<\/p>\n<h4>Effort estimate<\/h4>\n<p>Tasks for this project are estimated to take 20 hours to complete, depending on complexity. This is an estimate and not a schedule requirement; you choose when and how to work. Tasks must be submitted by the deadline and meet the listed acceptance criteria to be accepted.<\/p>\n<h4>Compensation<\/h4>\n<p>Up to $50\/hr equivalent, depending on level and pace. Tasks are estimated at approximately 20 hours each; you set your own schedule.<\/p><\/p><p><\/p>

<p><h4>Description<\/h4>\n<p>Please submit your CV in English and indicate your level of English proficiency.<\/p>\n<p>Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment.<\/p>\n<h4>What this opportunity involves<\/h4>\n<p>We're building a dataset to evaluate AI coding agents - how well a model handles real-world developer tasks.<\/p>\n<p>You'll create challenging tasks and evaluation criteria within realistic simulated environments:<\/p>\n<ul>\n <li>Build realistic developer environments - a virtual company with codebase, infrastructure, and context (tickets, docs, conversations) that forms a believable development history<\/li>\n <li>Design tasks from intermediate states of these environments - craft the prompt, define what \"solved\" means, and ensure the task is solvable by an AI agent<\/li>\n <li>Write tests that verify agent solutions - accept all valid approaches and reject incorrect ones, neither too strict nor too lenient<\/li>\n <li>Iterate on tasks and tests based on QA feedback - review agent solutions, analyze failures, and refine until the evaluation is fair and robust<\/li>\n<\/ul>\n<h4>What this is not<\/h4>\n<ul>\n <li>Not data labeling<\/li>\n <li>Not prompt engineering<\/li>\n <li>Not writing code from scratch - the agent writes most of the code; you guide and evaluate<\/li>\n<\/ul>\n<h4>What we look for<\/h4>\n<ul>\n <li>5+ years in software development<\/li>\n <li>Core stack: Python (FastAPI), JavaScript\/TypeScript (React), Docker, Postgres, Kafka, Redis<\/li>\n <li>Experience writing tests (functional, integration)<\/li>\n <li>English proficiency - B2+<\/li>\n<\/ul>\n<h4>Why this is hard<\/h4>\n<p>Frontier models are already good at coding. Creating a task that genuinely challenges the best models is non-trivial. You need to deeply understand where models fail and what scenarios reveal the difference between a good and a bad solution. Tasks have many valid solutions - writing tests that accept all correct solutions and reject incorrect ones is harder than it sounds.<\/p>\n<h4>How it works<\/h4>\n<p>Apply? Pass qualification(s)? Join a project? Complete tasks? Get paid<\/p>\n<h4>Effort estimate<\/h4>\n<p>Tasks for this project are estimated to take 20 hours to complete, depending on complexity. This is an estimate and not a schedule requirement; you choose when and how to work. Tasks must be submitted by the deadline and meet the listed acceptance criteria to be accepted.<\/p>\n<h4>Compensation<\/h4>\n<p>Up to $50\/hr equivalent, depending on level and pace. Tasks are estimated at approximately 20 hours each; you set your own schedule.<\/p><\/p><p><\/p>

<p><h4>Description<\/h4>\n<p>Please submit your CV in English and indicate your level of English proficiency.<\/p>\n<p>Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment.<\/p>\n<h4>What this opportunity involves<\/h4>\n<p>We're building a dataset to evaluate AI coding agents - how well a model handles real-world developer tasks.<\/p>\n<p>You'll create challenging tasks and evaluation criteria within realistic simulated environments:<\/p>\n<ul>\n<li>Build realistic developer environments - a virtual company with codebase, infrastructure, and context (tickets, docs, conversations) that forms a believable development history<\/li>\n<li>Design tasks from intermediate states of these environments - craft the prompt, define what \"solved\" means, and ensure the task is solvable by an AI agent<\/li>\n<li>Write tests that verify agent solutions - accept all valid approaches and reject incorrect ones, neither too strict nor too lenient<\/li>\n<li>Iterate on tasks and tests based on QA feedback - review agent solutions, analyze failures, and refine until the evaluation is fair and robust<\/li>\n<\/ul>\n<h4>What this is not<\/h4>\n<ul>\n<li>Not data labeling<\/li>\n<li>Not prompt engineering<\/li>\n<li>Not writing code from scratch - the agent writes most of the code; you guide and evaluate<\/li>\n<\/ul>\n<h4>What we look for<\/h4>\n<ul>\n<li>5+ years in software development<\/li>\n<li>Core stack: Python (FastAPI), JavaScript\/TypeScript (React), Docker, Postgres, Kafka, Redis<\/li>\n<li>Experience writing tests (functional, integration)<\/li>\n<li>English proficiency - B2+<\/li>\n<\/ul>\n<h4>Why this is hard<\/h4>\n<p>Frontier models are already good at coding. Creating a task that genuinely challenges the best models is non-trivial. You need to deeply understand where models fail and what scenarios reveal the difference between a good and a bad solution. Tasks have many valid solutions - writing tests that accept all correct solutions and reject incorrect ones is harder than it sounds.<\/p>\n<h4>How it works<\/h4>\n<p>Apply ? Pass qualification(s) ? Join a project ? Complete tasks ? Get paid<\/p>\n<h4>Effort estimate<\/h4>\n<p>Tasks for this project are estimated to take 20 hours to complete, depending on complexity. This is an estimate and not a schedule requirement; you choose when and how to work. Tasks must be submitted by the deadline and meet the listed acceptance criteria to be accepted.<\/p>\n<h4>Compensation<\/h4>\n<p>Up to $50\/hr equivalent, depending on level and pace. Tasks are estimated at ~20 hours each; you set your own schedule.<\/p><\/p><p><\/p>

<p><h4>Description<\/h4>\n<p>Please submit your CV in English and indicate your level of English proficiency.<\/p>\n<p>Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment.<\/p>\n<h4>What this opportunity involves<\/h4>\n<p>We're building a dataset to evaluate AI coding agents - how well a model handles real-world developer tasks.<\/p>\n<p>You'll create challenging tasks and evaluation criteria within realistic simulated environments:<\/p>\n<ul>\n<li>Build realistic developer environments - a virtual company with codebase, infrastructure, and context (tickets, docs, conversations) that forms a believable development history<\/li>\n<li>Design tasks from intermediate states of these environments - craft the prompt, define what \"solved\" means, and ensure the task is solvable by an AI agent<\/li>\n<li>Write tests that verify agent solutions - accept all valid approaches and reject incorrect ones, neither too strict nor too lenient<\/li>\n<li>Iterate on tasks and tests based on QA feedback - review agent solutions, analyze failures, and refine until the evaluation is fair and robust<\/li>\n<\/ul>\n<h4>What this is not<\/h4>\n<ul>\n<li>Not data labeling<\/li>\n<li>Not prompt engineering<\/li>\n<li>Not writing code from scratch - the agent writes most of the code; you guide and evaluate<\/li>\n<\/ul>\n<h4>What we look for<\/h4>\n<ul>\n<li>5+ years in software development<\/li>\n<li>Core stack: Python (FastAPI), JavaScript\/TypeScript (React), Docker, Postgres, Kafka, Redis<\/li>\n<li>Experience writing tests (functional, integration)<\/li>\n<li>English proficiency - B2+<\/li>\n<\/ul>\n<h4>Why this is hard<\/h4>\n<p>Frontier models are already good at coding. Creating a task that genuinely challenges the best models is non-trivial. You need to deeply understand where models fail and what scenarios reveal the difference between a good and a bad solution. Tasks have many valid solutions - writing tests that accept all correct solutions and reject incorrect ones is harder than it sounds.<\/p>\n<h4>How it works<\/h4>\n<p>Apply ? Pass qualification(s) ? Join a project ? Complete tasks ? Get paid<\/p>\n<h4>Effort estimate<\/h4>\n<p>Tasks for this project are estimated to take 20 hours to complete, depending on complexity. This is an estimate and not a schedule requirement; you choose when and how to work. Tasks must be submitted by the deadline and meet the listed acceptance criteria to be accepted.<\/p>\n<h4>Compensation<\/h4>\n<p>Up to $50\/hr equivalent, depending on level and pace. Tasks are estimated at approximately 20 hours each; you set your own schedule.<\/p><\/p><p><\/p>

<p><h4>Description<\/h4>\n<p>Please submit your CV in English and indicate your level of English proficiency.<\/p>\n<p>Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment.<\/p>\n<h4>What this opportunity involves<\/h4>\n<p>We're building a dataset to evaluate AI coding agents - how well a model handles real-world developer tasks.<\/p>\n<p>You'll create challenging tasks and evaluation criteria within realistic simulated environments:<\/p>\n<ul>\n <li>Build realistic developer environments - a virtual company with codebase, infrastructure, and context (tickets, docs, conversations) that forms a believable development history<\/li>\n <li>Design tasks from intermediate states of these environments - craft the prompt, define what \"solved\" means, and ensure the task is solvable by an AI agent<\/li>\n <li>Write tests that verify agent solutions - accept all valid approaches and reject incorrect ones, neither too strict nor too lenient<\/li>\n <li>Iterate on tasks and tests based on QA feedback - review agent solutions, analyze failures, and refine until the evaluation is fair and robust<\/li>\n<\/ul>\n<h4>What this is not<\/h4>\n<ul>\n <li>Not data labeling<\/li>\n <li>Not prompt engineering<\/li>\n <li>Not writing code from scratch - the agent writes most of the code; you guide and evaluate<\/li>\n<\/ul>\n<h4>What we look for<\/h4>\n<ul>\n <li>5+ years in software development<\/li>\n <li>Core stack: Python (FastAPI), JavaScript\/TypeScript (React), Docker, Postgres, Kafka, Redis<\/li>\n <li>Experience writing tests (functional, integration)<\/li>\n <li>English proficiency - B2+<\/li>\n<\/ul>\n<h4>Why this is hard<\/h4>\n<p>Frontier models are already good at coding. Creating a task that genuinely challenges the best models is non-trivial. You need to deeply understand where models fail and what scenarios reveal the difference between a good and a bad solution. Tasks have many valid solutions - writing tests that accept all correct solutions and reject incorrect ones is harder than it sounds.<\/p>\n<h4>How it works<\/h4>\n<p>Apply \u2192 Pass qualification(s) \u2192 Join a project \u2192 Complete tasks \u2192 Get paid<\/p>\n<h4>Effort estimate<\/h4>\n<p>Tasks for this project are estimated to take 20 hours to complete, depending on complexity. This is an estimate and not a schedule requirement; you choose when and how to work. Tasks must be submitted by the deadline and meet the listed acceptance criteria to be accepted.<\/p>\n<h4>Compensation<\/h4>\n<p>Up to $50\/hr equivalent, depending on level and pace. Tasks are estimated at approximately 20 hours each; you set your own schedule.<\/p><\/p><p><\/p>

<p><h4>Description</h4> <p>Remote junior AI engineer – computer vision<br> Location: Remote<br> Employment type: Full-time (8 hours) remotely<br> Experience level: Junior (5+ years)</p> <p>InnovationTeam is a forward-thinking technology company that delivers advanced AI and data-driven solutions across multiple industries. We are currently seeking a junior AI engineer – computer vision to join our AI engineering team.</p> <p>As a junior computer vision engineer at InnovationTeam, you will be responsible for designing, developing, and deploying vision-based AI systems for real-world, production environments. You will work closely with cross-functional teams to build scalable image and video analytics solutions.</p> <p>This position requires strong expertise in computer vision, deep learning, and software engineering. The ideal candidate is technically strong, self-driven, and experienced in taking AI models from research to production.</p> <p>At InnovationTeam, we foster a culture of innovation, collaboration, and technical excellence, offering an environment where junior engineers can make a meaningful impact.</p> <h4>Role overview</h4> <p>We are seeking a skilled AI engineer with a strong focus on computer vision to develop, optimize, and deploy vision-based AI solutions. The role involves working on real-world image and video analytics problems and delivering production-ready AI systems.</p> <h4>Requirements</h4> <ul> <li>Develop and train computer vision models for image and video analysis.</li> <li>Implement solutions for object detection, image classification, segmentation, and tracking.</li> <li>Prepare and manage datasets, including data cleaning, labelling, and augmentation.</li> <li>Optimize models for GPU performance, inference speed, and scalability.</li> <li>Deploy AI models into production using APIs and containerized services.</li> <li>Integrate computer vision models with broader AI and analytics platforms.</li> <li>Collaborate with software engineers, data scientists, and product teams.</li> <li>Maintain documentation and ensure code quality and reproducibility.</li> </ul> <h4>Required skills & qualifications</h4> <ul> <li>Minimum 2 years of hands-on experience in AI / machine learning / deep learning with a focus on computer vision.</li> <li>Master’s degree in computer science, software engineering, artificial intelligence, engineering, or a related field.</li> <li>Strong knowledge of computer vision concepts and algorithms.</li> <li>Practical experience with CNN-based models and modern CV architectures.</li> <li>Proficiency in Python and common ML/CV libraries (PyTorch or TensorFlow, OpenCV).</li> <li>Experience with object detection and segmentation frameworks (e.g., YOLO, Detectron2).</li> <li>Understanding of model evaluation, metrics, and performance optimization.</li> <li>Experience deploying models in cloud or on-prem environments.</li> <li>Familiarity with Docker and basic MLOps practices.</li> <li>Excellent English communication skills (written and spoken).</li> </ul> <h4>Nice to have</h4> <ul> <li>Experience with video analytics or real-time inference.</li> <li>Exposure to vision transformers or multimodal AI.</li> <li>Experience with GPU-based training and inference.</li> <li>Knowledge of cloud platforms (OCI, AWS, Azure, or GCP).</li> <li>Background in domains such as healthcare, smart cities, or industrial AI.</li> </ul> <h4>Benefits</h4> <ul> <li>Work on practical, production-grade computer vision solutions.</li> <li>Access to GPU infrastructure and modern AI tooling.</li> <li>Collaborative, engineering-focused work environment.</li> <li>Opportunities for growth and advanced AI exposure.</li> <li>Competitive compensation package.</li> </ul></p><p></p>

<p><h4>Description</h4> <p>InnovationTeam is a forward-thinking technology company that delivers advanced AI and data-driven solutions across multiple industries. We are currently seeking a junior AI engineer – computer vision to join our AI engineering team.</p> <p>As a junior computer vision engineer at InnovationTeam, you will be responsible for designing, developing, and deploying vision-based AI systems for real-world, production environments. You will work closely with cross-functional teams to build scalable image and video analytics solutions.</p> <p>This position requires strong expertise in computer vision, deep learning, and software engineering. The ideal candidate is technically strong, self-driven, and experienced in taking AI models from research to production.</p> <p>At InnovationTeam, we foster a culture of innovation, collaboration, and technical excellence, offering an environment where junior engineers can make a meaningful impact.</p> <h4>Role overview</h4> <p>We are seeking a skilled AI engineer with a strong focus on computer vision to develop, optimize, and deploy vision-based AI solutions. The role involves working on real-world image and video analytics problems and delivering production-ready AI systems.</p> <h4>Key responsibilities</h4> <ul> <li>Develop and train computer vision models for image and video analysis.</li> <li>Implement solutions for object detection, image classification, segmentation, and tracking.</li> <li>Prepare and manage datasets, including data cleaning, labeling, and augmentation.</li> <li>Optimize models for GPU performance, inference speed, and scalability.</li> <li>Deploy AI models into production using APIs and containerized services.</li> <li>Integrate computer vision models with broader AI and analytics platforms.</li> <li>Collaborate with software engineers, data scientists, and product teams.</li> <li>Maintain documentation and ensure code quality and reproducibility.</li> </ul> <h4>Required skills & qualifications</h4> <ul> <li>Minimum 2 years of hands-on experience in AI, machine learning, or deep learning with a focus on computer vision.</li> <li>Master’s degree in computer science, software engineering, artificial intelligence, engineering, or a related field.</li> <li>Strong knowledge of computer vision concepts and algorithms.</li> <li>Practical experience with CNN-based models and modern CV architectures.</li> <li>Proficiency in Python and common ML/CV libraries (PyTorch or TensorFlow, OpenCV).</li> <li>Experience with object detection and segmentation frameworks (e.g., YOLO, Detectron2).</li> <li>Understanding of model evaluation, metrics, and performance optimization.</li> <li>Experience deploying models in cloud or on-prem environments.</li> <li>Familiarity with Docker and basic MLOps practices.</li> <li>Excellent English communication skills (written and spoken).</li> </ul> <h4>Nice to have</h4> <ul> <li>Experience with video analytics or real-time inference.</li> <li>Exposure to vision transformers or multimodal AI.</li> <li>Experience with GPU-based training and inference.</li> <li>Knowledge of cloud platforms (OCI, AWS, Azure, or GCP).</li> <li>Background in domains such as healthcare, smart cities, or industrial AI.</li> </ul> <h4>What we offer</h4> <ul> <li>Work on practical, production-grade computer vision solutions.</li> <li>Access to GPU infrastructure and modern AI tooling.</li> <li>Collaborative, engineering-focused work environment.</li> <li>Opportunities for growth and advanced AI exposure.</li> <li>Competitive compensation package.</li> </ul></p><p></p>

<p><h4>Description</h4> <p>InnovationTeam is a forward-thinking technology company that delivers advanced AI and data-driven solutions across multiple industries. We are currently seeking a junior AI engineer – computer vision to join our AI engineering team.</p> <p>As a junior computer vision engineer at InnovationTeam, you will be responsible for designing, developing, and deploying vision-based AI systems for real-world, production environments. You will work closely with cross-functional teams to build scalable image and video analytics solutions.</p> <p>This position requires strong expertise in computer vision, deep learning, and software engineering. The ideal candidate is technically strong, self-driven, and experienced in taking AI models from research to production.</p> <p>At InnovationTeam, we foster a culture of innovation, collaboration, and technical excellence, offering an environment where junior engineers can make a meaningful impact.</p> <h4>Role overview</h4> <p>We are seeking a skilled AI engineer with a strong focus on computer vision to develop, optimize, and deploy vision-based AI solutions. The role involves working on real-world image and video analytics problems and delivering production-ready AI systems.</p> <h4>Key responsibilities</h4> <ul> <li>Develop and train computer vision models for image and video analysis.</li> <li>Implement solutions for object detection, image classification, segmentation, and tracking.</li> <li>Prepare and manage datasets, including data cleaning, labeling, and augmentation.</li> <li>Optimize models for GPU performance, inference speed, and scalability.</li> <li>Deploy AI models into production using APIs and containerized services.</li> <li>Integrate computer vision models with broader AI and analytics platforms.</li> <li>Collaborate with software engineers, data scientists, and product teams.</li> <li>Maintain documentation and ensure code quality and reproducibility.</li> </ul> <h4>Required skills & qualifications</h4> <ul> <li>Minimum 2 years of hands-on experience in AI, machine learning, or deep learning with a focus on computer vision.</li> <li>Master’s degree in computer science, software engineering, artificial intelligence, engineering, or a related field.</li> <li>Strong knowledge of computer vision concepts and algorithms.</li> <li>Practical experience with CNN-based models and modern CV architectures.</li> <li>Proficiency in Python and common ML/CV libraries (PyTorch or TensorFlow, OpenCV).</li> <li>Experience with object detection and segmentation frameworks (e.g., YOLO, Detectron2).</li> <li>Understanding of model evaluation, metrics, and performance optimization.</li> <li>Experience deploying models in cloud or on-prem environments.</li> <li>Familiarity with Docker and basic MLOps practices.</li> <li>Excellent English communication skills (written and spoken).</li> </ul> <h4>Nice to have</h4> <ul> <li>Experience with video analytics or real-time inference.</li> <li>Exposure to vision transformers or multimodal AI.</li> <li>Experience with GPU-based training and inference.</li> <li>Knowledge of cloud platforms (OCI, AWS, Azure, or GCP).</li> <li>Background in domains such as healthcare, smart cities, or industrial AI.</li> </ul> <h4>What we offer</h4> <ul> <li>Work on practical, production-grade computer vision solutions.</li> <li>Access to GPU infrastructure and modern AI tooling.</li> <li>Collaborative, engineering-focused work environment.</li> <li>Opportunities for growth and advanced AI exposure.</li> <li>Competitive compensation package.</li> </ul></p><p></p>

<p><h4>Description</h4> <p>Remote junior AI engineer – computer vision<br> Location: Remote<br> Employment type: Full-time (8 hours) remotely<br> Experience level: Junior (5+ years)</p> <p>InnovationTeam is a forward-thinking technology company that delivers advanced AI and data-driven solutions across multiple industries. We are currently seeking a junior AI engineer – computer vision to join our AI engineering team.</p> <p>As a junior computer vision engineer at InnovationTeam, you will be responsible for designing, developing, and deploying vision-based AI systems for real-world, production environments. You will work closely with cross-functional teams to build scalable image and video analytics solutions.</p> <p>This position requires strong expertise in computer vision, deep learning, and software engineering. The ideal candidate is technically strong, self-driven, and experienced in taking AI models from research to production.</p> <p>At InnovationTeam, we foster a culture of innovation, collaboration, and technical excellence, offering an environment where junior engineers can make a meaningful impact.</p> <h4>Role overview</h4> <p>We are seeking a skilled AI engineer with a strong focus on computer vision to develop, optimize, and deploy vision-based AI solutions. The role involves working on real-world image and video analytics problems and delivering production-ready AI systems.</p> <h4>Requirements</h4> <ul> <li>Develop and train computer vision models for image and video analysis.</li> <li>Implement solutions for object detection, image classification, segmentation, and tracking.</li> <li>Prepare and manage datasets, including data cleaning, labelling, and augmentation.</li> <li>Optimize models for GPU performance, inference speed, and scalability.</li> <li>Deploy AI models into production using APIs and containerized services.</li> <li>Integrate computer vision models with broader AI and analytics platforms.</li> <li>Collaborate with software engineers, data scientists, and product teams.</li> <li>Maintain documentation and ensure code quality and reproducibility.</li> </ul> <h4>Required skills & qualifications</h4> <ul> <li>Minimum 2 years of hands-on experience in AI / machine learning / deep learning with a focus on computer vision.</li> <li>Master’s degree in computer science, software engineering, artificial intelligence, engineering, or a related field.</li> <li>Strong knowledge of computer vision concepts and algorithms.</li> <li>Practical experience with CNN-based models and modern CV architectures.</li> <li>Proficiency in Python and common ML / CV libraries (PyTorch or TensorFlow, OpenCV).</li> <li>Experience with object detection and segmentation frameworks (e.g., YOLO, Detectron2).</li> <li>Understanding of model evaluation, metrics, and performance optimization.</li> <li>Experience deploying models in cloud or on-prem environments.</li> <li>Familiarity with Docker and basic MLOps practices.</li> <li>Excellent English communication skills (written and spoken).</li> </ul> <h4>Nice to have</h4> <ul> <li>Experience with video analytics or real-time inference.</li> <li>Exposure to vision transformers or multimodal AI.</li> <li>Experience with GPU-based training and inference.</li> <li>Knowledge of cloud platforms (OCI, AWS, Azure, or GCP).</li> <li>Background in domains such as healthcare, smart cities, or industrial AI.</li> </ul> <h4>Benefits</h4> <ul> <li>Work on practical, production-grade computer vision solutions.</li> <li>Access to GPU infrastructure and modern AI tooling.</li> <li>Collaborative, engineering-focused work environment.</li> <li>Opportunities for growth and advanced AI exposure.</li> <li>Competitive compensation package.</li> </ul></p><p></p>

<section><p class="heading jdMain">Job Description</p><p class="heading">Roles &amp; Responsibilities</p><div class="paragraph"><p><b>Position Summary </b>We are seeking a motivated Junior ERPNext / Frappe Engineer to support the implementation, configuration, customization, and ongoing enhancement of our ERP platform built on ERPNext and the Frappe Framework. The successful candidate will work closely with business stakeholders and internal teams to assist in translating operational requirements into ERP solutions, support business process automation initiatives, and help maintain the organization s ERP environment. This role offers an excellent opportunity to gain hands-on experience across multiple ERP modules, business functions, and enterprise technology initiatives. This is primarily an onsite position with occasional remote work flexibility. Key Responsibilities ERP Configuration &amp; Implementation Support Assist in configuring ERPNext modules according to business requirements. Support implementation activities across: Finance &amp; Accounting CRM &amp; Sales Procurement Inventory &amp; Warehousing Human Resources Projects Assets Service Management Configure forms, fields, roles, permissions, notifications, and workflows. Participate in system setup, testing, deployment, and post-go-live support activities. Business Process Support Document existing business processes and operational requirements. Assist in mapping business processes into ERP workflows. Help identify process improvement and automation opportunities. Support preparation of functional and technical documentation. Data Migration &amp; System Maintenance Prepare, validate, and import business data into ERPNext. Assist with data cleansing and migration activities. Support routine system maintenance and configuration updates. Help troubleshoot user issues and system errors. Frappe Development &amp; Customization Assist in developing and maintaining customizations using the Frappe Framework. Create basic: Custom Fields Reports Print Formats Dashboards Scripts Support development and testing of integrations with third-party systems. Participate in code reviews and testing activities. User Support &amp; Training Provide first-level support to ERP users. Assist with user onboarding and training sessions. Create user guides and system documentation. Track and resolve support requests in a timely manner. Testing &amp; Quality Assurance Execute functional testing and user acceptance testing activities. Validate workflows and business rules. Document issues and support resolution efforts. Ensure implemented solutions meet business requirements.</p></div></section><section><p class="heading">Desired Candidate Profile</p><p class="paragraph"></p><ul><li>Bachelor's degree in Computer Science, Information Systems, Software Engineering, Business Information Technology, or a related field.</li><li>1 3 years of experience in ERP systems, business applications, software development, or system implementation.</li><li>Basic understanding of ERP concepts and business processes.</li><li>Knowledge of: ERPNext (preferred) Frappe Framework (preferred) Python JavaScript SQL databases REST APIs</li><li>Strong analytical and problem-solving skills.</li><li>Ability to learn new technologies quickly.</li><li>Strong communication and documentation skills.</li><li>Preferred Qualifications Exposure to ERPNext or Frappe projects.</li><li>Experience with business process documentation.</li><li>Familiarity with Linux environments.</li><li>Knowledge of accounting, procurement, HR, or inventory management processes.</li><li>Experience with Git version control.</li><li>ERPNext or Frappe training/certifications.</li></ul><p>Key Competencies</p><ul><li>Attention to Detail</li><li>Problem Solving</li><li>Process Thinking</li><li>Team Collaboration</li><li>Technical Curiosity</li><li>Communication Skills</li><li>Organization and Documentation</li><li>Customer Service Mindset</li><li>Adaptability and Continuous Learning</li></ul><p>Success Measures</p><p>The successful candidate will:</p><ul><li>Effectively support ERPNext implementation projects.</li><li>Deliver accurate system configurations and documentation.</li><li>Resolve user issues efficiently.</li><li>Contribute to process automation and system improvements.</li><li>Maintain high-quality data and system integrity.</li><li>Continuously develop ERPNext, Frappe, and business process expertise.</li></ul><p></p></section>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <span>Please submit your CV in English and indicate your level of English proficiency.<br> Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems.<br> Participation isproject-based, not permanent employment.<br> What this opportunity involves While each project involves unique tasks, contributors may: Design original material engineering problems that simulate real engineering workflows; Create problems requiring Python programming to solve engineering calculations and simulations; Ensure problems are computationally intensive and require numerical methods or iterative solutions; Develop problems involving system design, optimization, and analysis; Base problems on real research challenges or practical applications from engineering practice; Verify solutions using Python with standard engineering libraries; Document problem statements clearly and provide verified correct answers.<br> What we look for This opportunity is a good fit for material scientists &amp; engineers with an experience in python open to part-time, non-permanent projects.<br> Ideally, contributors will have: Degree in Material Science or related fields; Python proficiency for numerical validation.<br> MATLAB, R, C, SQL, Numpy, Pandas, SciPy, domain-specific libraries, Stata or knowledge of any programming language can be equivalent; 2+ years of professional experience: applied, research, or teaching experience is applicable; Understanding of practical engineering constraints and approximations; Strong written English (C1+).<br> How it works Apply → Pass qualification(s) → Join a project → Complete tasks → Get paid Project time expectations For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements.<br> This is an estimate, not a guaranteed workload, and applies only while the project is active.<br> Compensation On this project, contributors can earn up to $35 per hour equivalent , depending on their level and pace of contribution.<br> Compensation varies across projects depending on scope, complexity, and required expertise.<br> Please note that other projects on the platform may offer different earning levels based on their requirements.<br></span> </div>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <span>Please submit your CV in English and indicate your level of English proficiency.<br> Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems.<br> Participation is project-based, not permanent employment.<br> What this opportunity involves While each project involves unique tasks, contributors may: Design original computational physics problems that simulate real physics research workflows; Create problems requiring Python programming to solve (using Numpy, SciPy, Sympy); Ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks); Develop problems requiring non-trivial reasoning chains in mechanics, electromagnetism, thermodynamics, and quantum mechanics; Base problems on real research challenges or practical applications from physics practice; Verify solutions using Python with standard physics simulation libraries; Document problem statements clearly and provide verified correct answers.<br> What we look for This opportunity is a good fit for optical engineers with an experience in python open to part-time, non-permanent projects.<br> Ideally, contributors will have: Degree in Physics (Theoretical, Experimental, or Computational) or related fields; Python proficiency for numerical validation.<br> MATLAB, R, C, SQL, Numpy, Pandas, SciPy, domain-specific libraries, Stata or knowledge of any programming language can be equivalent; 2+ years of professional experience: applied, research, or teaching experience is applicable; Experience with numerical simulation methods; Ability to design problems that mirror real physics research workflows; Creative thinking in problem design across diverse physics areas; Familiarity with physics modeling and approximation techniques; Strong written English (C1+).<br> How it works Apply → Pass qualification(s) → Join a project → Complete tasks → Get paid Project time expectations For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements.<br> This is an estimate, not a guaranteed workload, and applies only while the project is active.<br> Compensation On this project, contributors can earn up to $35 per hour equivalent , depending on their level and pace of contribution.<br> Compensation varies across projects depending on scope, complexity, and required expertise.<br> Please note that other projects on the platform may offer different earning levels based on their requirements.<br></span> </div>

<p><h4>About Jeeny</h4> <p>In 2014, a joint venture between iMENA Group and Rocket Internet was created to address the issues of fragmentation and inefficiency that were facing the Jordanian and Saudi taxi markets. Using technology to consolidate the market and build a ride-hailing service provider in Jordan and Saudi Arabia was the solution that they came up with.</p> <p>When iMENA was introduced to the idea of a ride-hailing solution, it saw the opportunity of transforming the transportation industry with a disruptive business model. iMENA started with Jeeny (EasyTaxi at the time) early on as strategic partners; it joined forces and collaborated on optimizing marketing and operations, and worked with the authorities to shape the industry’s regulatory framework.</p> <p>Jeeny hit the market with a vision of making people’s everyday lives easier by providing a simple innovative solution to a real problem. All the while, Jeeny has had a tremendous economic impact on the drivers who make the service possible, amplifying the network effect of the model and propelling the service towards scalability and growth.</p> <p>Today, Jeeny has evolved beyond ride-hailing to become a comprehensive on-demand logistics marketplace with a large fleet of private car and taxi cab drivers in its key markets. Whether it’s food, groceries, or business correspondence that people need to move around town, Jeeny is the go-to name in Jordan and Saudi Arabia.</p> <p>We have offices in Riyadh, Jeddah, Madinah, Amman, Lahore & Karachi.</p> <h4>Program Overview</h4> <p>Are you ready to accelerate your career and solve real-world problems from day one?</p> <p>The Jeeny Graduate Trainee Program 2026 is designed for ambitious graduates who want to grow into the next generation of leaders at Jeeny.</p> <p>This program offers direct exposure to senior leadership, high-impact business challenges, and fast-track learning opportunities across key functions of the business.</p> <p>If you're curious, analytical, and ready to take ownership early in your career, this program will give you the platform to grow.</p> <p><strong>Application deadline:</strong> July 18, 2026. We recommend applying early as applications may close once we receive sufficient interest.</p> <p>Over a 6-month rotation, you will work on real business challenges across multiple teams while collaborating closely with senior leaders and decision-makers.</p> <p>You will gain experience in areas such as:</p> <ul> <li><strong>Commercial (Growth & Pricing)</strong><br>Design data-driven strategies to improve driver and passenger engagement while strengthening customer loyalty. Analyze market data and optimize pricing strategies to maximize marketplace efficiency and revenue.</li> <li><strong>Product</strong><br>Collaborate with product and engineering teams to identify user problems, design solutions, and help bring impactful features to life.</li> <li><strong>Business Finance</strong><br>Work with financial and operational data to support strategic decision-making and improve business efficiency.</li> <li><strong>Performance Marketing</strong><br>Monetization engine of Jeeny where you’ll manage in-app advertising campaigns and analyze marketing analytics to optimize campaign performance and drive revenue growth.</li> </ul> <p>Throughout the program, you will work closely with cross-functional teams and senior leaders to drive meaningful business outcomes.</p> <h4>What You Will Do</h4> <p>As part of the program, you will take ownership of real business challenges and contribute directly to strategic initiatives.</p> <p>Your responsibilities may include:</p> <ul> <li>Analyzing complex datasets to identify insights and recommend data-driven solutions</li> <li>Designing and implementing strategies to improve business performance</li> <li>Supporting key business projects that impact drivers, passengers, and marketplace growth</li> <li>Conducting market and competitive research to identify opportunities</li> <li>Developing new processes and frameworks to improve operational efficiency</li> <li>Running experiments and pilot initiatives to test new ideas</li> <li>Collaborating with cross-functional teams including product, finance, marketing, and operations</li> <li>Contributing to strategic discussions and initiatives alongside senior leadership</li> </ul> <p>This is a hands-on role where your ideas, insights, and ownership can create real impact from day one.</p> <h4>Requirements</h4> <p>We are looking for graduates who are analytical, curious, and driven to solve complex problems.</p> <ul> <li>Bachelor’s degree from an accredited university (graduating by August 2026)</li> <li>Strong analytical and problem-solving skills</li> <li>Familiarity with analytical tools such as Python, R, SQL, or similar</li> <li>Proficiency in statistical analysis and data interpretation</li> <li>Strong communication and collaboration skills</li> <li>Ability to work in fast-paced and evolving environments</li> <li>Curiosity, initiative, and willingness to challenge the status quo</li> <li>A collaborative mindset and passion for building impact solutions</li> </ul> <h4>Application Process</h4> <p>Once you submit your application, shortlisted candidates will go through the following stages:</p> <ul> <li>Application review</li> <li>Case study assessment</li> <li>Interviews</li> <li>Final selection</li> </ul> <p>During the process, we will evaluate your problem-solving ability, analytical thinking, and motivation to contribute to Jeeny’s mission.</p> <h4>Benefits</h4> <ul> <li>An opportunity to collaborate with talented individuals while learning, growing, and expanding your skill set</li> <li>An environment that encourages you to take ownership and produce excellent outcomes every day</li> <li>Health benefits and life insurance</li> <li>Hybrid work model</li> <li>Flexible working hours</li> <li>Monthly codes to commute freely</li> </ul> <h4>Start Your Leadership Journey</h4> <p>If you are ready to learn fast, take ownership, and grow alongside experienced leaders, we encourage you to apply.</p> <p>Join us in building the future of mobility.</p> <p>Apply now to the Jeeny Graduate Trainee Program 2026.</p> <h4>Why Join Jeeny?</h4> <ul> <li>Be part of one of the leading mobility platforms in the region.</li> <li>Work in a dynamic and collaborative environment.</li> <li>Opportunity to lead impactful finance initiatives and process improvements.</li> <li>Career growth and professional development opportunities.</li> </ul></p><p></p>

<p><h4>About Jeeny</h4> <p>In 2014, a joint venture between iMENA Group and Rocket Internet was created to address the issues of fragmentation and inefficiency that were facing the Jordanian and Saudi taxi markets. Using technology to consolidate the market and build a ride-hailing service provider in Jordan and Saudi Arabia was the solution that they came up with.</p> <p>When iMENA was introduced to the idea of a ride-hailing solution, it saw the opportunity of transforming the transportation industry with a disruptive business model. iMENA started with Jeeny (EasyTaxi at the time) early on as strategic partners; it joined forces and collaborated on optimizing marketing and operations, and worked with the authorities to shape the industry’s regulatory framework.</p> <p>Jeeny hit the market with a vision of making people’s everyday lives easier by providing a simple innovative solution to a real problem. All the while, Jeeny has had a tremendous economic impact on the drivers who make the service possible, amplifying the network effect of the model and propelling the service towards scalability and growth.</p> <p>Today, Jeeny has evolved beyond ride-hailing to become a comprehensive on-demand logistics marketplace with a large fleet of private car and taxi cab drivers in its key markets. Whether it’s food, groceries, or business correspondence that people need to move around town, Jeeny is the go-to name in Jordan and Saudi Arabia.</p> <p>We have offices in Riyadh, Jeddah, Madinah, Amman, Lahore & Karachi.</p> <h4>Program Overview</h4> <p>Are you ready to accelerate your career and solve real-world problems from day one?</p> <p>The Jeeny Graduate Trainee Program 2026 is designed for ambitious graduates who want to grow into the next generation of leaders at Jeeny.</p> <p>This program offers direct exposure to senior leadership, high-impact business challenges, and fast-track learning opportunities across key functions of the business.</p> <p>If you're curious, analytical, and ready to take ownership early in your career, this program will give you the platform to grow.</p> <p><strong>Application deadline:</strong> July 18, 2026. We recommend applying early as applications may close once we receive sufficient interest.</p> <p>Over a 6-month rotation, you will work on real business challenges across multiple teams while collaborating closely with senior leaders and decision-makers.</p> <p>You will gain experience in areas such as:</p> <ul> <li><strong>Commercial (Growth & Pricing)</strong><br>Design data-driven strategies to improve driver and passenger engagement while strengthening customer loyalty. Analyze market data and optimize pricing strategies to maximize marketplace efficiency and revenue.</li> <li><strong>Product</strong><br>Collaborate with product and engineering teams to identify user problems, design solutions, and help bring impactful features to life.</li> <li><strong>Business Finance</strong><br>Work with financial and operational data to support strategic decision-making and improve business efficiency.</li> <li><strong>Performance Marketing</strong><br>Monetization engine of Jeeny where you’ll manage in-app advertising campaigns and analyze marketing analytics to optimize campaign performance and drive revenue growth.</li> </ul> <p>Throughout the program, you will work closely with cross-functional teams and senior leaders to drive meaningful business outcomes.</p> <h4>What You Will Do</h4> <p>As part of the program, you will take ownership of real business challenges and contribute directly to strategic initiatives.</p> <p>Your responsibilities may include:</p> <ul> <li>Analyzing complex datasets to identify insights and recommend data-driven solutions</li> <li>Designing and implementing strategies to improve business performance</li> <li>Supporting key business projects that impact drivers, passengers, and marketplace growth</li> <li>Conducting market and competitive research to identify opportunities</li> <li>Developing new processes and frameworks to improve operational efficiency</li> <li>Running experiments and pilot initiatives to test new ideas</li> <li>Collaborating with cross-functional teams including product, finance, marketing, and operations</li> <li>Contributing to strategic discussions and initiatives alongside senior leadership</li> </ul> <p>This is a hands-on role where your ideas, insights, and ownership can create real impact from day one.</p> <h4>Requirements</h4> <p>We are looking for graduates who are analytical, curious, and driven to solve complex problems.</p> <ul> <li>Bachelor’s degree from an accredited university (graduating by August 2026)</li> <li>Strong analytical and problem-solving skills</li> <li>Familiarity with analytical tools such as Python, R, SQL, or similar</li> <li>Proficiency in statistical analysis and data interpretation</li> <li>Strong communication and collaboration skills</li> <li>Ability to work in fast-paced and evolving environments</li> <li>Curiosity, initiative, and willingness to challenge the status quo</li> <li>A collaborative mindset and passion for building impact solutions</li> </ul> <h4>Application Process</h4> <p>Once you submit your application, shortlisted candidates will go through the following stages:</p> <ul> <li>Application review</li> <li>Case study assessment</li> <li>Interviews</li> <li>Final selection</li> </ul> <p>During the process, we will evaluate your problem-solving ability, analytical thinking, and motivation to contribute to Jeeny’s mission.</p> <h4>Benefits</h4> <ul> <li>An opportunity to collaborate with talented individuals while learning, growing, and expanding your skill set</li> <li>An environment that encourages you to take ownership and produce excellent outcomes every day</li> <li>Health benefits and life insurance</li> <li>Hybrid work model</li> <li>Flexible working hours</li> <li>Monthly codes to commute freely</li> </ul> <h4>Start Your Leadership Journey</h4> <p>If you are ready to learn fast, take ownership, and grow alongside experienced leaders, we encourage you to apply.</p> <p>Join us in building the future of mobility.</p> <p>Apply now to the Jeeny Graduate Trainee Program 2026.</p> <h4>Why Join Jeeny?</h4> <ul> <li>Be part of one of the leading mobility platforms in the region.</li> <li>Work in a dynamic and collaborative environment.</li> <li>Opportunity to lead impactful finance initiatives and process improvements.</li> <li>Career growth and professional development opportunities.</li> </ul></p><p></p>