Ophthalmology Jobs in Jordan

<p><h4>Description</h4> <p>Please submit your CV in English and indicate your level of English proficiency.</p> <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> <h4>What this opportunity involves</h4> <p>While each project involves unique tasks, contributors may:</p> <ul> <li>Evaluate AI-generated mortgage underwriting decisions across loan types (conforming, jumbo, FHA, VA, cash-out refinance);</li> <li>Create test cases involving qualifying income calculations for self-employed borrowers using Schedule C, K-1, and Schedule E;</li> <li>Draft and audit conditional approval letters and adverse action notices for Reg B / ECOA compliance;</li> <li>Distinguish Fannie Mae / Freddie Mac selling guide rules from lender overlays in jumbo and non-conforming loan scenarios;</li> <li>Document problem statements clearly and provide verified correct answers.</li> </ul> <h4>What we look for</h4> <p>This opportunity is a good fit for mortgage underwriters and loan origination professionals open to part-time, non-permanent projects. Ideally, contributors will have:</p> <ul> <li>Degree in Finance, Economics, Business Administration, Accounting, Real Estate, or any related field;</li> <li>3+ years of mortgage, lending, real estate, or financial services experience;</li> <li>Current or recent experience in underwriting and origination or adjacent roles;</li> <li>Ability to calculate qualifying income for self-employed borrowers from IRS Forms 1040, Schedule C, Schedule E, and K-1;</li> <li>Deep familiarity with Fannie Mae / Freddie Mac selling guides and knowledge of Reg B, Reg Z, and TRID disclosure timing rules;</li> <li>Strong written English (C1+).</li> </ul> <h4>How it works</h4> <p>Apply → Pass qualification(s) → Join a project → Complete tasks → Get paid</p> <h4>Project time expectations</h4> <p>For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active.</p> <h4>Compensation</h4> <p>On this project, contributors can earn up to $50 per hour equivalent, depending on their level and pace of contribution.</p> <p>Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.</p></p><p></p>

<p><h4>Please submit your CV in English and indicate your level of English proficiency.<\/h4>\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>8+ 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 30 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><\/p><p><\/p>

<p><h4>The opportunity</h4> <p>EY is looking for an assistant manager to join FAAS team to lead on complex advisory engagements and support growth of the business.</p> <h4>Your key responsibilities</h4> <p>As an assistant manager, you'll participate in client engagements, contributing in both financial and non-financial service sectors. You’ll collaborate with the manager and client to determine a FAAS strategy that appropriately addresses risk and manages client expectations relating to deliverables, while ensuring FAAS engagement teams understand the client's needs and expectations and that the work product is client-focused, clear, accurate and well-presented.</p> <p>Timely delivery of projects in compliance with regulatory frameworks is essential, as is working with other service lines in providing an integrated service delivery.</p> <h4>Skills and attributes for success</h4> <p>Pro-activity, accountability and results-driven people will flourish in this environment. Dealing with competing priorities, understanding how to manage resources and communicating effectively are key skills. This will have a huge impact on those around you and help promote a positive work ethic.</p> <h4>To qualify for the role, you must have</h4> <ul> <li>A bachelor's degree and approximately 2 to 4 years of related work experience</li> <li>An undergraduate or master's degree in accounting and/or another appropriate academic major</li> <li>CPA, CA, or ACCA certification</li> <li>Big 4 experience (audit or advisory) and particular business or industry experience to meet special needs</li> </ul> <h4>What we offer you</h4> <p>At EY, we’ll develop you with future-focused skills and equip you with world-class experiences. We’ll empower you in a flexible environment, and fuel you and your extraordinary talents in a diverse and inclusive culture of globally connected teams.</p> <p>Are you ready to shape your future with confidence? Apply today.</p> <p>To help create an equitable and inclusive experience during the recruitment process, please inform us as soon as possible about any disability-related adjustments or accommodations you may need.</p> <h4>EY | Building a better working world</h4> <p>EY is building a better working world by creating new value for clients, people, society and the planet, while building trust in capital markets.</p> <p>Enabled by data, AI and advanced technology, EY teams help clients shape the future with confidence and develop answers for the most pressing issues of today and tomorrow.</p> <p>EY teams work across a full spectrum of services in assurance, consulting, tax, strategy and transactions. Fueled by sector insights, a globally connected, multi-disciplinary network and diverse ecosystem partners, EY teams can provide services in more than 150 countries and territories.</p></p><p></p>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <span>Please submit your resume 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 Annotation is what helps AI make sense of the world.<br> As an annotator, you may be invited to take part in online projects such as rating AI-generated content, evaluating factual accuracy, or comparing responses — when projects are available.<br> While each project involves unique tasks, contributors may: Carefully review provided data (text, images, or videos); Label or classify content based on project guidelines; Identify and flag factually incorrect, sensitive, inappropriate, or unclear material.<br> What we look for This opportunity is a good fit for candidates open to part-time, non-permanent projects.<br> Ideally, contributors will have: Bachelor’s degree in any discipline; Minimum 1 year of experience in any professional role; Logical thinking, fact-checking and reasoning abilities; Strong attention to detail and ability to understand and follow complex instructions; Strong communication skills, including the ability to ask clarifying questions when needed; Genuine interest in technology and artificial intelligence; Strong written and spoken English (C1+).<br> How it works Apply → Pass qualification(s) → Join a project (when available) → Complete tasks → Get paid Why this freelance opportunity might be a great fit for you Take part in a part-time, remote, freelance project that fits around your primary professional or academic commitments; Participate into advanced AI projects and gain valuable experience that enhances your portfolio; Influence how future AI models understand and communicate in your field of expertise.<br> 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> Tasks must be submitted by the deadline and meet the listed acceptance criteria to be accepted.<br> Compensation Paid per accepted task.<br> Your rate depends on the qualification tier you reach and how efficiently you complete tasks — up to the equivalent of $15/hr .<br> Because payment is per task, a faster pace raises your effective hourly rate.<br> Keep in mind, quality standards must be maintained, regardless of speed.<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: 8+ 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 paidEffort estimate Tasks for this project are estimated to take 30 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 $150/hr equivalent , depending on level and pace.<br> Tasks are estimated at ~30 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> <p>Please submit your CV in English and indicate your level of English proficiency.</p> <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> <h4>What this opportunity involves</h4> <p>While each project involves unique tasks, contributors may:</p> <ul> <li>Design original computational physics problems that simulate real physics research workflows;</li> <li>Create problems requiring Python programming to solve (using Numpy, SciPy, Sympy);</li> <li>Ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks);</li> <li>Develop problems requiring non-trivial reasoning chains in mechanics, electromagnetism, thermodynamics, and quantum mechanics;</li> <li>Base problems on real research challenges or practical applications from physics practice;</li> <li>Verify solutions using Python with standard physics simulation libraries;</li> <li>Document problem statements clearly and provide verified correct answers.</li> </ul> <h4>What we look for</h4> <p>This opportunity is a good fit for physicists with experience in Python open to part-time, non-permanent projects. Ideally, contributors will have:</p> <ul> <li>Degree in Physics (Theoretical, Experimental, or Computational) or related fields;</li> <li>Python proficiency for numerical validation. MATLAB, R, C, SQL, Numpy, Pandas, SciPy, domain-specific libraries, Stata or knowledge of any programming language can be equivalent;</li> <li>2+ years of professional experience: applied, research, or teaching experience is applicable;</li> <li>Experience with numerical simulation methods;</li> <li>Ability to design problems that mirror real physics research workflows;</li> <li>Creative thinking in problem design across diverse physics areas;</li> <li>Familiarity with physics modeling and approximation techniques;</li> <li>Strong written English (C1+).</li> </ul> <h4>How it works</h4> <p>Apply → Pass qualification(s) → Join a project → Complete tasks → Get paid</p> <h4>Project time expectations</h4> <p>For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active.</p> <h4>Compensation</h4> <p>On this project, contributors can earn up to $35 per hour equivalent, depending on their level and pace of contribution.</p> <p>Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.</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 ~20 hours each; you set your own schedule.<\/p><\/p><p><\/p>

<p><h4>Description</h4> <p>Please submit your CV in English and indicate your level of English proficiency.</p> <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> <h4>What this opportunity involves</h4> <p>While each project involves unique tasks, contributors may:</p> <ul> <li>Design and evaluate rule application scenarios — reading a compliance artifact (advertisement, disclosure, policy) against a specific regulation and citing the exact subsection that applies or is violated;</li> <li>Write sanctions alert disposition cases with structured false-positive reasoning documentation and escalation scenarios;</li> <li>Build compliance testing scenarios: sample selection, test design, findings documentation, and examiner-ready conclusion memos;</li> <li>Develop policy gap identification cases where an internal policy is silent on a regulatory requirement, contradicts the regulation, or has not been updated to reflect a recent change;</li> <li>Document all test cases with verified regulatory citations to the specific subsection — never approximated, never fabricated.</li> </ul> <h4>What we look for</h4> <p>This opportunity is a good fit for professionals with a background in compliance, regulatory affairs, legal services, or broader financial services who are open to part-time, non-permanent projects. Ideally, contributors will have:</p> <ul> <li>Degree in Law, Finance, Economics, Business Administration, Accounting, or any related field;</li> <li>2+ years of compliance, audit, legal, risk management, or financial services experience;</li> <li>Current or recent experience in compliance and regulatory roles, financial crimes, or adjacent roles;</li> <li>Citation discipline as a core habit — able to identify the exact regulatory subsection that applies and flag uncertainty rather than approximate;</li> <li>CRCM, CAMS, or equivalent local credential is a strong positive signal; former regulatory examiner or inspector status is equally strong;</li> <li>Strong written English (C1+).</li> </ul> <h4>How it works</h4> <p>Apply? Pass qualification(s)? Join a project? Complete tasks? Get paid.</p> <h4>Project time expectations</h4> <p>For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active.</p> <h4>Compensation</h4> <p>On this project, contributors can earn up to $50 per hour equivalent, depending on their level and pace of contribution.</p> <p>Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.</p></p><p></p>

<p><h4>Description</h4> <p>Please submit your CV in English and indicate your level of English proficiency.</p> <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> <h4>What this opportunity involves</h4> <p>While each project involves unique tasks, contributors may:</p> <ul> <li>Design and evaluate rule application scenarios — reading a compliance artifact (advertisement, disclosure, policy) against a specific regulation and citing the exact subsection that applies or is violated;</li> <li>Write sanctions alert disposition cases with structured false-positive reasoning documentation and escalation scenarios;</li> <li>Build compliance testing scenarios: sample selection, test design, findings documentation, and examiner-ready conclusion memos;</li> <li>Develop policy gap identification cases where an internal policy is silent on a regulatory requirement, contradicts the regulation, or has not been updated to reflect a recent change;</li> <li>Document all test cases with verified regulatory citations to the specific subsection — never approximated, never fabricated.</li> </ul> <h4>What we look for</h4> <p>This opportunity is a good fit for professionals with a background in compliance, regulatory affairs, legal services, or broader financial services who are open to part-time, non-permanent projects. Ideally, contributors will have:</p> <ul> <li>Degree in Law, Finance, Economics, Business Administration, Accounting, or any related field;</li> <li>2+ years of compliance, audit, legal, risk management, or financial services experience;</li> <li>Current or recent experience in compliance and regulatory roles, financial crimes, or adjacent roles;</li> <li>Citation discipline as a core habit — able to identify the exact regulatory subsection that applies and flag uncertainty rather than approximate;</li> <li>CRCM, CAMS, or equivalent local credential is a strong positive signal; former regulatory examiner or inspector status is equally strong;</li> <li>Strong written English (C1+).</li> </ul> <h4>How it works</h4> <p>Apply? Pass qualification(s)? Join a project? Complete tasks? Get paid.</p> <h4>Project time expectations</h4> <p>For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active.</p> <h4>Compensation</h4> <p>On this project, contributors can earn up to $50 per hour equivalent, depending on their level and pace of contribution.</p> <p>Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.</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> <p>Please submit your CV in English and indicate your level of English proficiency.</p> <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> <h4>What this opportunity involves</h4> <p>While each project involves unique tasks, contributors may:</p> <ul> <li>Design and evaluate rule application scenarios — reading a compliance artifact (advertisement, disclosure, policy) against a specific regulation and citing the exact subsection that applies or is violated;</li> <li>Write sanctions alert disposition cases with structured false-positive reasoning documentation and escalation scenarios;</li> <li>Build compliance testing scenarios: sample selection, test design, findings documentation, and examiner-ready conclusion memos;</li> <li>Develop policy gap identification cases where an internal policy is silent on a regulatory requirement, contradicts the regulation, or has not been updated to reflect a recent change;</li> <li>Document all test cases with verified regulatory citations to the specific subsection — never approximated, never fabricated.</li> </ul> <h4>What we look for</h4> <p>This opportunity is a good fit for professionals with a background in compliance, regulatory affairs, legal services, or broader financial services who are open to part-time, non-permanent projects. Ideally, contributors will have:</p> <ul> <li>Degree in Law, Finance, Economics, Business Administration, Accounting, or any related field;</li> <li>2+ years of compliance, audit, legal, risk management, or financial services experience;</li> <li>Current or recent experience in compliance and regulatory roles, financial crimes, or adjacent roles;</li> <li>Citation discipline as a core habit — able to identify the exact regulatory subsection that applies and flag uncertainty rather than approximate;</li> <li>CRCM, CAMS, or equivalent local credential is a strong positive signal; former regulatory examiner or inspector status is equally strong;</li> <li>Strong written English (C1+).</li> </ul> <h4>How it works</h4> <p>Apply? Pass qualification(s)? Join a project? Complete tasks? Get paid.</p> <h4>Project time expectations</h4> <p>For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active.</p> <h4>Compensation</h4> <p>On this project, contributors can earn up to $50 per hour equivalent, depending on their level and pace of contribution.</p> <p>Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.</p></p><p></p>

<p><h4>Description</h4> <p>Please submit your CV in English and indicate your level of English proficiency.</p> <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> <h4>What this opportunity involves</h4> <p>While each project involves unique tasks, contributors may:</p> <ul> <li>Design and evaluate rule application scenarios — reading a compliance artifact (advertisement, disclosure, policy) against a specific regulation and citing the exact subsection that applies or is violated;</li> <li>Write sanctions alert disposition cases with structured false-positive reasoning documentation and escalation scenarios;</li> <li>Build compliance testing scenarios: sample selection, test design, findings documentation, and examiner-ready conclusion memos;</li> <li>Develop policy gap identification cases where an internal policy is silent on a regulatory requirement, contradicts the regulation, or has not been updated to reflect a recent change;</li> <li>Document all test cases with verified regulatory citations to the specific subsection — never approximated, never fabricated.</li> </ul> <h4>What we look for</h4> <p>This opportunity is a good fit for professionals with a background in compliance, regulatory affairs, legal services, or broader financial services who are open to part-time, non-permanent projects. Ideally, contributors will have:</p> <ul> <li>Degree in Law, Finance, Economics, Business Administration, Accounting, or any related field;</li> <li>2+ years of compliance, audit, legal, risk management, or financial services experience;</li> <li>Current or recent experience in compliance and regulatory roles, financial crimes, or adjacent roles;</li> <li>Citation discipline as a core habit — able to identify the exact regulatory subsection that applies and flag uncertainty rather than approximate;</li> <li>CRCM, CAMS, or equivalent local credential is a strong positive signal; former regulatory examiner or inspector status is equally strong;</li> <li>Strong written English (C1+).</li> </ul> <h4>How it works</h4> <p>Apply? Pass qualification(s)? Join a project? Complete tasks? Get paid.</p> <h4>Project time expectations</h4> <p>For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active.</p> <h4>Compensation</h4> <p>On this project, contributors can earn up to $50 per hour equivalent, depending on their level and pace of contribution.</p> <p>Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.</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>\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>

<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: 8+ 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 paidEffort estimate Tasks for this project are estimated to take 30 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 $150/hr equivalent , depending on level and pace.<br> Tasks are estimated at ~30 hours each; you set your own schedule.<br></span> </div>