Machine operator Jobs

<p><h4>Position summary</h4> <p>Respond and attend to guest repair requests. Communicate with guests/customers to resolve maintenance issues. Perform preventive maintenance on tools and kitchen and mechanical room equipment, including cleaning and lubrication. Visually inspect tools, equipment, or machines. Carry equipment (e.g., tools, radio). Identify, locate, and operate all shut-off valves for equipment and all utility shut-offs for buildings. Maintain maintenance inventory and requisition parts and supplies as needed. Communicate each day’s activities and problems that occur to the other shifts using approved communication programs and standards.</p> <p>Display basic knowledge or ability to acquire knowledge in the following categories: air conditioning and refrigeration, electrical, mechanical, plumbing, pneumatic/electronic systems and controls, carpentry and finish skills, kitchen equipment, vehicles, energy conservation, and/or general building. Perform all surface preparation, painting, minor drywall and wood trim repair, light bulb and A/C filter replacement and the complete and thorough cleanup of the painting or repair area.</p> <p>Test, troubleshoot and perform basic repair on all types of equipment, plumbing (e.g., plunge toilets and unclog drains), electrical components including lamps, cosmetic items, extension cords, vacuum cleaners, internet devices, replace electrical switches and outlets, and other guestroom items. Program TVs and perform general housekeeping and engineering-related inventory duties. Use the Lockout/Tagout system before performing any maintenance work. Perform repairs on interior and exterior landscaping as well as external landscaping sprinklers. Display basic computer skills including inputting air handler schedules and making temperature changes.</p> <p>Follow all company and safety and security policies and procedures; report any maintenance problems, safety hazards, accidents, or injuries; complete safety training and certifications; and properly store flammable materials. Ensure uniform and personal appearance are clean and professional, maintain confidentiality of proprietary information, and protect company assets.</p> <p>Welcome and acknowledge all guests according to company standards, anticipate and address guests’ service needs, assist</p><p></p>

<p>We are seeking a talented Machine Learning Engineer to join our data science team. The ideal candidate will be responsible for developing and implementing machine learning models and algorithms that solve complex business problems. You will work closely with data scientists, software engineers, and stakeholders to deliver scalable solutions.</p><ul><li>Design, build, and deploy machine learning models and algorithms.</li><li>Collaborate with data scientists to refine data features and enhance model performance.</li><li>Optimize and improve existing machine learning models for efficiency and accuracy.</li><li>Conduct data preprocessing, feature engineering, and data analysis.</li><li>Monitor and maintain models in production to ensure they operate effectively.</li><li>Document and communicate model designs and performance metrics to stakeholders.</li><li>Stay updated on the latest industry trends and advancements in machine learning and AI.</li><li>Participate in code reviews and contribute to a culture of continuous improvement.</li><li>Perform statistical analysis, and train and retrain systems to optimize performance.</li><li>Familiarity with version control systems (e.g., Git) and CI/CD practices.</li><li>Experience with AI/GenAI.</li><li>Experience with AWS data services (e.g., AWS EMR, AWS Glue, AWS Athena).</li><li>Design/build and deploy API services.</li></ul><p><strong>Desired Candidate Profile</strong></p><ul><li>Bachelor's degree in Computer Science, Data Science, Mathematics, or a related field.</li><li>Proven experience as a Machine Learning Engineer or in a similar role.</li><li>Proficiency in programming languages such as Python.</li><li>Experience with machine learning frameworks and libraries (e.g.,AWS BedRock, Amazon SageMaker, TensorFlow, PyTorch, Scikit-learn).</li><li>Strong understanding of algorithms, data structures, and software engineering principles.</li><li>Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and tools for deploying machine learning models.</li><li>Knowledge of data manipulation and analysis tools (e.g., SQL, Pandas, NumPy).</li><li>Excellent problem-solving skills and ability to work collaboratively in a team environment.</li><li>Experience with deep learning and natural language processing (NLP) techniques.</li><li>Understanding of model interpretability and explainability.</li></ul>

<p>The Back End LSM Mechanic is responsible for the maintenance, repair, and troubleshooting of all Machine (LSM) equipment and associated machinery in the back-end production process. This role ensures optimal machine performance, minimizes downtime, and contributes to the overall efficiency and quality of can manufacturing operations.</p><p><strong>Job Responsibilities:</strong></p><ul><li>Perform routine preventive maintenance on LSM Machines, ensuring all components are functioning correctly and efficiently.</li><li>Diagnose and troubleshoot mechanical, electrical, and pneumatic issues on LSM equipment, identifying root causes and implementing effective solutions.</li><li>Execute repairs, overhauls, and replacements of machine parts, including motors, gears, bearings, sensors, and control systems.</li><li>Conduct regular inspections of LSMs to detect potential problems early and proactively address them to prevent breakdowns.</li><li>Collaborate with production operators and other maintenance staff to optimize machine settings and improve operational efficiency.</li><li>Maintain accurate records of maintenance activities, including repairs performed, parts used, and machine performance data.</li><li>Adhere to all safety regulations and company policies, ensuring a safe working environment.</li><li>Assist in the installation and commissioning of new LSM equipment and upgrades.</li><li>Participate in continuous improvement initiatives aimed at enhancing machine reliability and reducing maintenance costs.</li></ul><p><strong>Desired Candidate Profile</strong></p><ul><li>High School Diploma or equivalent; a technical diploma or certification in mechanical, electrical, or industrial maintenance is highly preferred.</li><li>Proven experience (minimum 1-2 years) as a maintenance mechanic, specifically with LMS Machines or similar high-speed industrial machinery in a manufacturing environment.</li><li>Strong understanding of mechanical systems, hydraulics, pneumatics, and basic electrical circuits.</li><li>Ability to read and interpret technical manuals, schematics, and blueprints.</li><li>Proficiency in using various hand and power tools, as well as diagnostic equipment.</li><li>Excellent troubleshooting and problem-solving skills, with a keen eye for detail.</li><li>Ability to work independently and as part of a team in a fast-paced manufacturing setting.</li><li>Strong communication skills, both written and verbal.</li><li>Willingness to work shifts, weekends, and holidays as required by production schedules.</li><li>Physical ability to lift heavy objects, stand for extended periods, and work in various environmental conditions.</li></ul>

<p>Responsibilities:<br>Design, build, and deploy machine learning models and algorithms.<br>Collaborate with data scientists to refine data features and enhance model performance.<br>Optimize and improve existing machine learning models for efficiency and accuracy.<br>Conduct data preprocessing, feature engineering, and data analysis.<br>Monitor and maintain models in production to ensure they operate effectively.<br>Document and communicate model designs and performance metrics to stakeholders.<br>Stay updated on the latest industry trends and advancements in machine learning and AI.<br>Participate in code reviews and contribute to a culture of continuous improvement.</p><p><strong>Desired Candidate Profile</strong></p><p>Profile requirements:<br>Bachelor's degree in Computer Science, Data Science, Mathematics, or a related field.<br>Proven experience as a Machine Learning Engineer or in a similar role.<br>Proficiency in programming languages such as Python, Java, or R.<br>Experience with machine learning frameworks and libraries (e.g.,AWS BedRock, Amazon SageMaker, TensorFlow, PyTorch, Scikit-learn).<br>Strong understanding of algorithms, data structures, and software engineering principles.<br>Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and tools for deploying machine learning models.<br>Knowledge of data manipulation and analysis tools (e.g., SQL, Pandas, NumPy).<br>Excellent problem-solving skills and ability to work collaboratively in a team environment.<br>Experience with deep learning and natural language processing (NLP) techniques.<br>Understanding of model interpretability and explainability.<br>Perform statistical analysis, and train and retrain systems to optimize performance</p>

<p> <b>Job Description:</b> </p> <p> </p> <p>Main challenges &amp; complexity</p> <p>Keep the machine in good operating condition and reducing the repairing cost by maintaining the machine as much as need, also he has to work in some cases in a stressful environment with tight deadlines, like the change size or labels for Back End Necker Mechanic.</p> <p><b><br></b></p><p><b>Job Summary:**</b></p> <p>The Back End Necker Mechanic is responsible for the maintenance, repair, and troubleshooting of all Machine equipment and associated machinery in the back-end production process. This role ensures optimal machine performance, minimizes downtime, and contributes to the overall efficiency and quality of can manufacturing operations.</p> <p><b><br></b></p><p><b>Job Responsibilities:**</b></p> <p>* Perform routine preventive maintenance on Back End Necker Mechanic, ensuring all components are functioning correctly and efficiently.</p> <p>* Diagnose and troubleshoot mechanical, electrical, and pneumatic issues on Back End Necker equipment, identifying root causes and implementing effective solutions.</p> <p>* Execute repairs, overhauls, and replacements of machine parts, including motors, gears, bearings, sensors, and control systems.</p> <p>* Conduct regular inspections of Back End Necker to detect potential problems early and proactively address them to prevent breakdowns.</p> <p>* Collaborate with production operators and other maintenance staff to optimize machine settings and improve operational efficiency.</p> <p>* Maintain accurate records of maintenance activities, including repairs performed, parts used, and machine performance data.</p> <p>* Adhere to all safety regulations and company policies, ensuring a safe working environment.</p> <p>* Assist in the installation and commissioning of new Back End Necker equipment and upgrades.</p> <p>* Participate in continuous improvement initiatives aimed at enhancing machine reliability and reducing maintenance costs.</p><p><strong>Desired Candidate Profile</strong></p><p>Job Qualifications:**</p> <p>* High School Diploma or equivalent; a technical diploma or certification in mechanical, electrical, or industrial maintenance is highly preferred.</p> <p>* Proven experience (minimum 1-2 years) as a maintenance mechanic, specifically with Back End Necker or similar high-speed industrial machinery in a manufacturing environment.</p> <p>* Strong understanding of mechanical systems, hydraulics, pneumatics, and basic electrical circuits.</p> <p>* Ability to read and interpret technical manuals, schematics, and blueprints.</p> <p>* Proficiency in using various hand and power tools, as well as diagnostic equipment.</p> <p>* Excellent troubleshooting and problem-solving skills, with a keen eye for detail.</p> <p>* Ability to work independently and as part of a team in a fast-paced manufacturing setting.</p> <p>* Strong communication skills, both written and verbal.</p> <p>* Willingness to work shifts, weekends, and holidays as required by production schedules.</p> <p>* Physical ability to lift heavy objects, stand for extended periods, and work in various environmental conditions.</p>

<p><h4>Description</h4> <p>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.</p> <p>Working closely with business stakeholders, product teams, and technical experts, you'll transform business challenges into scalable analytical, machine learning, and GenAI solutions. 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.</p> <h4>Requirements</h4> <h4>What you'll do</h4> <ul> <li>Collaborate with business stakeholders to identify and prioritize AI and analytics opportunities</li> <li>Translate business requirements into scalable data science and machine learning solutions</li> <li>Validate data availability and define analytical approaches for new use cases</li> <li>Build predictive models, machine learning solutions, and GenAI applications</li> <li>Design robust data pipelines and analytical workflows</li> <li>Apply data processing, feature engineering, and statistical modelling techniques</li> <li>Ensure solutions are scalable, production-ready, and aligned with software engineering and MLOps best practices</li> <li>Present analytical findings and recommendations to technical and executive stakeholders</li> <li>Communicate AI capabilities, feasibility, risks, and expected business value in a clear and practical way</li> <li>Mentor junior team members and support technical delivery across multiple initiatives</li> </ul> <h4>You're our match if you have</h4> <ul> <li>Master's degree in data science, computer science, artificial intelligence, mathematics, software engineering, or a related field</li> <li>5+ years of hands-on experience delivering data science or machine learning solutions</li> <li>Strong Python programming skills and experience with modern data science libraries</li> <li>Experience building predictive models, machine learning solutions, and GenAI applications</li> <li>Strong understanding of statistics, data modelling, and feature engineering</li> <li>Experience designing scalable data pipelines and production-ready AI solutions</li> <li>Familiarity with MLOps, model deployment, and machine learning lifecycle management</li> <li>Excellent stakeholder management and communication skills</li> <li>Ability to translate complex technical concepts into business value</li> </ul> <h4>Bonus points if you have experience with</h4> <ul> <li>Telecommunications or other customer-centric industries</li> <li>Large-scale customer analytics and segmentation</li> <li>Large language models (LLMs) and retrieval-augmented generation (RAG)</li> <li>Cloud platforms such as Azure, AWS, or Google Cloud</li> <li>Databricks, Spark, or distributed data processing</li> <li>Docker, Kubernetes, or CI/CD pipelines</li> <li>Leading or mentoring technical teams</li> </ul></p><p></p>

<p>1. JOB DETAILS:</p><p>Job Title: Analyst, ML Engineer</p><p>Reports to: Sr. Manager, IT Digital Platforms &amp; Digital Transformation</p><p>Department: IT Applications</p><p>Function: IT Applications</p><p>Company: Hikma Holding</p><p>2. JOB PURPOSE:</p><p>The ML Engineer is responsible for supporting the development, testing, and deployment of machine learning models and AI-powered pipelines across Hikma Pharmaceuticals. Working as part of the AI team under the Sr. Manager, IT Digital Platforms &amp; Digital Transformation, and under the close guidance of the AI Architect and AI developers team, this role provides hands-on ML engineering support across the solution lifecycle from data preparation and model experimentation through to deployment and monitoring. The ML Engineer is expected to develop their machine learning and data engineering skills rapidly within a structured team environment, contributing to Hikma's enterprise AI transformation while building foundational expertise in regulated pharmaceutical AI delivery.</p><p>3. JOB DIMENSIONS:</p><p>Number of Staff Supervised: Direct Reports Count: 0 (0 vacant)</p><p>Indirect Reports Count: N/A</p><p>Financial Budget (USD): Supports AI initiative delivery under team supervision</p><p>4. KEY ACCOUNTABILITIES:</p><p>ML Model Development &amp; Experimentation</p><ul><li>Support the development, training, and evaluation of machine learning models under the guidance of the AI Architect and senior team members, following approved architecture standards and initiative briefs</li><li>Assist in ML experimentation activities including data exploration, feature engineering, model selection, and performance evaluation using standard frameworks and cloud AI services</li><li>Apply foundational ML techniques across classical machine learning, NLP, and generative AI domains relevant to Hikma's business areas including Supply Chain, Quality, HR, and Commercial</li><li>Support the implementation of LLM-based solutions including RAG pipelines, prompt engineering, and embedding-based retrieval under senior technical guidance</li><li>Maintain experiment tracking logs, model versioning records, and reproducibility documentation using tools such as ML flow or Azure Machine Learning</li><li>Produce clear and accurate model development artefacts including experiment summaries, performance reports, and model documentation</li></ul><p>Data Engineering &amp; Feature Development</p><ul><li>Assist in building and maintaining ML data pipelines covering data ingestion, transformation, validation, and basic feature engineering for model training and inference workflows</li><li>Support data quality checks, anomaly detection, and dataset preparation activities to ensure ML model inputs meet required standards</li><li>Collaborate with the Data &amp; Analytics team to access and understand available data assets, following data governance and privacy guidelines</li><li>Work with structured data sources including relational databases and enterprise system extracts, developing proficiency in handling diverse data types over time</li></ul><p>ML-Ops &amp; Production Support</p><ul><li>Support the implementation and maintenance of ML-Ops pipeline components including model packaging, deployment, and basic performance monitoring under senior team guidance</li><li>Assist in deploying ML models to cloud environments using approved tooling (Azure Machine Learning, ML-flow, Docker, or equivalent)</li><li>Monitor deployed models for observable performance issues and flag anomalies to the AI Architect or senior team members for investigation</li><li>Maintain accurate records in model registries including versioning and change logs across AI initiatives</li><li>Contribute to the documentation and validation support activities for ML models deployed in GxP-regulated contexts, following defined compliance processes</li></ul><p>Quality Assurance &amp; Testing</p><ul><li>Support the development and execution of testing activities for ML solutions, including data, pipeline tests, model performance checks, and basic integration testing</li><li>Actively participate in code reviews and technical walkthroughs, applying feedback to improve code quality and engineering practices</li><li>Document assigned ML components clearly including data preparation steps, model configurations, test results, and known issues</li><li>Identify and escalate technical issues encountered across the ML stack in a timely and structured manner</li></ul><p>5. Behavioural Competencies:</p><p>Initiative &amp; Drive for Results - Very Good</p><p>Change &amp; Innovation - Very Good</p><p>Communication &amp; Influence - Good</p><p>Developing &amp; Empowering others - Good</p><p>Problem Solving &amp; decision Making - Excellent</p><p>Strategic Thinking - Good</p><p>6. Technical Competencies:</p><p>ML Model Development &amp; Experimentation - Good</p><p>Python &amp; ML Frameworks (PyTorch, TensorFlow, scikit-learn, HuggingFace) - Good</p><p>MLOps &amp; Model Lifecycle Tooling - Good</p><p>Data Engineering &amp; Pipeline Support - Good</p><p>Cloud AI/ML Services (Azure ML) - Good</p><p>Generative AI &amp; LLM Development (RAG, LangChain, Semantic Kernel) - Very Good</p><p>Model Explainability &amp; Responsible AI Awareness - Very Good</p><p>Containerization &amp; CI/CD Basics (Docker, Git, Azure DevOps) - Good</p><p>7. COMMUNICATIONS &amp; WORKING RELATIONSHIPS:</p><p>Internal: AI Champions Network, AI Architect, AI Developer, Data &amp; Analytics Team</p><p>External: AI/ML Vendors &amp; Solution Providers, Implementation Partners, Open Source &amp; Developer Communities</p><p><strong>Desired Candidate Profile</strong></p><ul><li>Bachelor's degree in computer science, Software Engineering, Data Science, Mathematics, Statistics, or related technical field *(Required)*</li><li>Master's degree in Artificial Intelligence, Machine Learning, Data Science, or Computer Science *(Preferred)*</li><li>Microsoft Azure AI Engineer Associate, AWS Machine Learning Specialty, or Google Professional ML Engineer certification *(Preferred)*</li><li>Relevant ML/AI certifications (e.g., DeepLearning.AI ML Specialization, Databricks ML Associate, fast.ai) *(Preferred)*</li><li>0-1 year of professional experience in software development, data science, machine learning, or a related technical field (fresh graduates are welcome to apply)</li><li>Demonstrated hands-on experience with ML model development through academic projects, internships, capstone projects, hackathons, or personal projects</li><li>Familiarity with cloud AI/ML platforms (Azure, AWS, or GCP) gained through coursework, self-study, or practical experimentation *(Preferred)*</li><li>Any exposure to generative AI, LLM tools, or RAG concepts through academic or personal projects *(Preferred)*</li><li>Pharmaceutical, healthcare, life sciences, or other regulated industry exposure *(Preferred but not expected)*</li><li>Working knowledge of Python and foundational ML/DL libraries including scikit-learn, pandas, NumPy, and at least one deep learning framework</li><li>Practical exposure to training and evaluating ML models including classical machine learning and at least one of: NLP, computer vision, or time-series analysis through academic, personal, or internship projects</li><li>Basic familiarity with generative AI concepts including Large Language Models, prompt engineering, and RAG principles *(Preferred)*</li><li>Awareness of ML-Ops concepts and tools such as ML-flow or Azure Machine Learning for experiment tracking and model management *(Preferred)*</li><li>Basic experience with data preparation, cleaning, transformation, and exploratory data analysis using Python</li><li>Familiarity with version control using Git and basic software development practices including code reviews and testing</li><li>Basic understanding of cloud platforms (Azure, AWS, or GCP) and awareness of cloud-based AI/ML services *(Preferred)*</li><li>Familiarity with containerization concepts (Docker) and CI/CD basics *(Preferred)*</li><li>Awareness of responsible AI principles, data privacy regulations (GDPR, HIPAA), and IT security practices relevant to ML development</li><li>Any familiarity with pharmaceutical business processes or GxP compliance in a technology context is a plus *(Preferred)*</li></ul>

<p><h4>Description</h4> <p>BlackStone eIT is actively looking for a dedicated AI team lead to spearhead our artificial intelligence initiatives. This role involves leading a talented team of AI professionals to create innovative AI-driven solutions that align with the company's vision. You will play a crucial part in strategizing, developing, and deploying AI technologies that enhance our products and services while maintaining the highest standards of excellence.</p> <h4>Responsibilities:</h4> <ul> <li>Lead the AI team in designing, developing, and implementing AI models and systems.</li> <li>Collaborate with stakeholders to identify AI opportunities that drive business value.</li> <li>Guide the team to effectively use machine learning frameworks and tools.</li> <li>Oversee project lifecycle from research and prototyping to production deployment.</li> <li>Maintain knowledge of latest trends and advancements in AI and machine learning.</li> <li>Establish best practices and foster a culture of continuous improvement and innovation.</li> </ul> <h4>Requirements</h4> <ul> <li>Experience: 6+ years of hands-on experience in machine learning, deep learning, or AI engineering.</li> <li>3+ years of experience in a technical leadership or mentoring role.</li> <li>Programming & frameworks: Expert-level proficiency in Python and deep learning frameworks (PyTorch is strongly preferred, or TensorFlow).</li> <li>Cloud infrastructure: Extensive, hands-on experience with Microsoft Azure, specifically building training and deployment pipelines using Azure ML workspace, MLflow, and container orchestration (Docker/Kubernetes).</li> <li>NLP expertise: Deep understanding of modern NLP architectures (Transformers, BERT, GPT variants), tokenization, vector databases, and libraries like Hugging Face and LangChain/LangGraph.</li> <li>CV expertise: Strong mathematical foundation in image processing and experience building custom models using OpenCV, YOLO architectures, and PyTorch Vision.</li> <li>MLOps: Proven ability to build CI/CD pipelines for machine learning models, manage model registries, and monitor model drift in production.</li> <li>Experience with building and deploying autonomous AI agents (e.g., using LangChain, LangGraph, Crew AI).</li> <li>Background in edge deployment for computer vision models (TensorRT, ONNX).</li> </ul> <h4>Benefits</h4> <ul> <li>Paid time off</li> <li>Performance bonus</li> <li>Training & development</li> </ul></p><p></p>

<p><h4>BlackStone eIT is actively looking for a dedicated AI team lead to spearhead our artificial intelligence initiatives.</h4> <p>This role involves leading a talented team of AI professionals to create innovative AI-driven solutions that align with the company's vision. You will play a crucial part in strategizing, developing, and deploying AI technologies that enhance our products and services while maintaining the highest standards of excellence.</p> <h4>Responsibilities:</h4> <ul> <li>Lead the AI team in designing, developing, and implementing AI models and systems.</li> <li>Collaborate with stakeholders to identify AI opportunities that drive business value.</li> <li>Guide the team to effectively use machine learning frameworks and tools.</li> <li>Oversee project lifecycle from research and prototyping to production deployment.</li> <li>Maintain knowledge of latest trends and advancements in AI and machine learning.</li> <li>Establish best practices and foster a culture of continuous improvement and innovation.</li> </ul> <h4>Requirements</h4> <ul> <li>Experience: 6+ years of hands-on experience in machine learning, deep learning, or AI engineering.</li> <li>3+ years of experience in a technical leadership or mentoring role.</li> <li>Programming & frameworks: Expert-level proficiency in Python and deep learning frameworks (PyTorch is strongly preferred, or TensorFlow).</li> <li>Cloud infrastructure: Extensive, hands-on experience with Microsoft Azure, specifically building training and deployment pipelines using Azure ML workspace, MLflow, and container orchestration (Docker/Kubernetes).</li> <li>NLP expertise: Deep understanding of modern NLP architectures (Transformers, BERT, GPT variants), tokenization, vector databases, and libraries like Hugging Face and Lang Chain/Lang Graph.</li> <li>CV expertise: Strong mathematical foundation in image processing and experience building custom models using OpenCV, YOLO architectures, and PyTorch Vision.</li> <li>MLOps: Proven ability to build CI/CD pipelines for machine learning models, manage model registries, and monitor model drift in production.</li> <li>Experience with building and deploying autonomous AI agents (e.g., using Langchain, Langgraph, Crew AI).</li> <li>Background in edge deployment for computer vision models (TensorRT, ONNX).</li> </ul> <h4>Benefits</h4> <ul> <li>Paid time off</li> <li>Performance bonus</li> <li>Training & development</li> </ul></p><p></p>

<p><h4>Description</h4> <p>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.</p> <p>Working closely with business stakeholders, product teams, and technical experts, you'll transform business challenges into scalable analytical, machine learning, and GenAI solutions. 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.</p> <h4>Requirements</h4> <h4>What you'll do</h4> <ul> <li>Collaborate with business stakeholders to identify and prioritize AI and analytics opportunities</li> <li>Translate business requirements into scalable data science and machine learning solutions</li> <li>Validate data availability and define analytical approaches for new use cases</li> <li>Build predictive models, machine learning solutions, and GenAI applications</li> <li>Design robust data pipelines and analytical workflows</li> <li>Apply data processing, feature engineering, and statistical modelling techniques</li> <li>Ensure solutions are scalable, production-ready, and aligned with software engineering and MLOps best practices</li> <li>Present analytical findings and recommendations to technical and executive stakeholders</li> <li>Communicate AI capabilities, feasibility, risks, and expected business value in a clear and practical way</li> <li>Mentor junior team members and support technical delivery across multiple initiatives</li> </ul> <h4>You're our match if you have</h4> <ul> <li>Master's degree in data science, computer science, artificial intelligence, mathematics, software engineering, or a related field</li> <li>5+ years of hands-on experience delivering data science or machine learning solutions</li> <li>Strong Python programming skills and experience with modern data science libraries</li> <li>Experience building predictive models, machine learning solutions, and GenAI applications</li> <li>Strong understanding of statistics, data modelling, and feature engineering</li> <li>Experience designing scalable data pipelines and production-ready AI solutions</li> <li>Familiarity with MLOps, model deployment, and machine learning lifecycle management</li> <li>Excellent stakeholder management and communication skills</li> <li>Ability to translate complex technical concepts into business value</li> </ul> <h4>Bonus points if you have experience with</h4> <ul> <li>Telecommunications or other customer-centric industries</li> <li>Large-scale customer analytics and segmentation</li> <li>Large language models (LLMs) and retrieval-augmented generation (RAG)</li> <li>Cloud platforms such as Azure, AWS, or Google Cloud</li> <li>Databricks, Spark, or distributed data processing</li> <li>Docker, Kubernetes, or CI/CD pipelines</li> <li>Leading or mentoring technical teams</li> </ul></p><p></p>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <span> <strong><span>1. JOB DETAILS:</span></strong> <br> <span>Job Title:</span> <span>Analyst, ML Engineer </span> <br> <span>Reports to:</span> <span>Sr. Manager, IT Digital Platforms &amp; Digital Transformation</span> <br> <span>Department:</span> <span>IT Applications </span> <br> <span>Function:</span> <span>IT Applications</span> <br> <span>Company:</span> <span>Hikma Holding</span> <br> <strong><span>2. JOB PURPOSE:</span></strong> <br> </span><p><span>The ML Engineer is responsible for supporting the development, testing, and deployment of machine learning models and AI-powered pipelines across Hikma Pharmaceuticals. Working as part of the AI team under the Sr. Manager, IT Digital Platforms &amp; Digital Transformation, and under the close guidance of the AI Architect and AI developers’ team, this role provides hands-on ML engineering support across the solution lifecycle — from data preparation and model experimentation through to deployment and monitoring. The ML Engineer is expected to develop their machine learning and data engineering skills rapidly within a structured team environment, contributing to Hikma's enterprise AI transformation while building foundational expertise in regulated pharmaceutical AI delivery.</span></p><br> <br> <strong><span>3. JOB DIMENSIONS:</span></strong> <br> <p><span>Number of Staff Supervised:</span></p><br> <p><span>Direct Reports Count:</span></p><br> <p><span>0 (0 vacant)</span></p><br> <br> <p><span>Indirect Reports Count:</span></p><br> <p><span>N/A</span></p><br> <br> <p><span>Financial Budget (USD):</span></p><br> <p><span>Supports AI initiative delivery under team supervision</span></p><br> <br> <p><span>4. KEY ACCOUNTABILITIES:</span></p><br> <br> <p><span>Description</span></p><br> <br> <p><strong><span>ML Model Development &amp; Experimentation</span></strong></p><br> <br> <ul> <li><span>Support the development, training, and evaluation of machine learning models under the guidance of the AI Architect and senior team members, following approved architecture standards and initiative briefs</span></li> <li><span>Assist in ML experimentation activities including data exploration, feature engineering, model selection, and performance evaluation using standard frameworks and cloud AI services</span></li> <li><span>Apply foundational ML techniques across classical machine learning, NLP, and generative AI domains relevant to Hikma's business areas including Supply Chain, Quality, HR, and Commercial</span></li> <li><span>Support the implementation of LLM-based solutions including RAG pipelines, prompt engineering, and embedding-based retrieval under senior technical guidance</span></li> <li><span>Maintain experiment tracking logs, model versioning records, and reproducibility documentation using tools such as ML flow or Azure Machine Learning</span></li> <li><span>Produce clear and accurate model development artefacts including experiment summaries, performance reports, and model documentation</span></li> </ul> <br> <p><strong><span>Data Engineering &amp; Feature Development</span></strong></p><br> <br> <ul> <li><span>Assist in building and maintaining ML data pipelines covering data ingestion, transformation, validation, and basic feature engineering for model training and inference workflows</span></li> <li><span>Support data quality checks, anomaly detection, and dataset preparation activities to ensure ML model inputs meet required standards</span></li> <li><span>Collaborate with the Data &amp; Analytics team to access and understand available data assets, following data governance and privacy guidelines</span></li> <li><span>Work with structured data sources including relational databases and enterprise system extracts, developing proficiency in handling diverse data types over time</span></li> </ul> <br> <p><strong><span>ML-Ops &amp; Production Support</span></strong></p><br> <br> <ul> <li><span>Support the implementation and maintenance of ML-Ops pipeline components including model packaging, deployment, and basic performance monitoring under senior team guidance</span></li> <li><span>Assist in deploying ML models to cloud environments using approved tooling (Azure Machine Learning, ML-flow, Docker, or equivalent)</span></li> <li><span>Monitor deployed models for observable performance issues and flag anomalies to the AI Architect or senior team members for investigation</span></li> <li><span>Maintain accurate records in model registries including versioning and change logs across AI initiatives</span></li> <li><span>Contribute to the documentation and validation support activities for ML models deployed in GxP-regulated contexts, following defined compliance processes</span></li> </ul> <br> <p><strong><span>Quality Assurance &amp; Testing</span></strong></p><br> <br> <ul> <li><span>Support the development and execution of testing activities for ML solutions, including data, pipeline tests, model performance checks, and basic integration testing</span></li> <li><span>Actively participate in code reviews and technical walkthroughs, applying feedback to improve code quality and engineering practices</span></li> <li><span>Document assigned ML components clearly including data preparation steps, model configurations, test results, and known issues</span></li> <li><span>Identify and escalate technical issues encountered across the ML stack in a timely and structured manner</span></li> </ul> <br> </div>

<p><h4>Description</h4> <p>BlackStone eIT is actively looking for a dedicated AI team lead to spearhead our artificial intelligence initiatives. This role involves leading a talented team of AI professionals to create innovative AI-driven solutions that align with the company's vision. You will play a crucial part in strategizing, developing, and deploying AI technologies that enhance our products and services while maintaining the highest standards of excellence.</p> <h4>Responsibilities:</h4> <ul> <li>Lead the AI team in designing, developing, and implementing AI models and systems.</li> <li>Collaborate with stakeholders to identify AI opportunities that drive business value.</li> <li>Guide the team to effectively use machine learning frameworks and tools.</li> <li>Oversee project lifecycle from research and prototyping to production deployment.</li> <li>Maintain knowledge of latest trends and advancements in AI and machine learning.</li> <li>Establish best practices and foster a culture of continuous improvement and innovation.</li> </ul> <h4>Requirements</h4> <ul> <li>Experience: 6+ years of hands-on experience in machine learning, deep learning, or AI engineering.</li> <li>3+ years of experience in a technical leadership or mentoring role.</li> <li>Programming & frameworks: Expert-level proficiency in Python and deep learning frameworks (PyTorch is strongly preferred, or TensorFlow).</li> <li>Cloud infrastructure: Extensive, hands-on experience with Microsoft Azure, specifically building training and deployment pipelines using Azure ML workspace, MLflow, and container orchestration (Docker/Kubernetes).</li> <li>NLP expertise: Deep understanding of modern NLP architectures (Transformers, BERT, GPT variants), tokenization, vector databases, and libraries like Hugging Face and LangChain/Lang Graph.</li> <li>CV expertise: Strong mathematical foundation in image processing and experience building custom models using OpenCV, YOLO architectures, and PyTorch Vision.</li> <li>MLOps: Proven ability to build CI/CD pipelines for machine learning models, manage model registries, and monitor model drift in production.</li> <li>Experience with building and deploying autonomous AI agents (e.g., using LangChain, Lang Graph, Crew AI).</li> <li>Background in edge deployment for computer vision models (TensorRT, ONNX).</li> </ul> <h4>Benefits</h4> <ul> <li>Paid time off</li> <li>Performance bonus</li> <li>Training & development</li> </ul></p><p></p>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <span>We are looking for a highly skilled L2 Oracle KVM Virtualization Engineer with strong hands-on experience in Oracle Linux KVM and libvirt within enterprise production environments.<br> The role will be responsible for managing KVM hypervisors, virtual machines, HA configurations, live migration, storage and network integration, performance optimization, patching, backup/DR, and production incident management .<br> The ideal candidate should have strong troubleshooting skills and experience supporting mission-critical infrastructure in 24x7 production and DR environments .<br> Key Responsibilities Install, configure, administer, and maintain Oracle Linux KVM hypervisors .<br> Manage the complete VM lifecycle , including provisioning, configuration, migration, and decommissioning.<br> Configure and support High Availability (HA) and live migration .<br> Manage storage integration with KVM hosts, including iSCSI, NFS, SAN, and FC .<br> Configure and troubleshoot virtual networking, including VLANs, bridges, and bonding .<br> Monitor virtualization platform health, performance, capacity, and availability.<br> Perform CPU, memory, and disk I/O performance tuning .<br> Apply hypervisor patches, Linux kernel updates, and security hardening.<br> Manage VM backup and restore activities in coordination with backup teams.<br> Support DR environments and VM replication strategies.<br> Troubleshoot host failures, VM crashes, resource contention, and virtualization performance issues.<br> Perform Root Cause Analysis (RCA) for production incidents.<br> Support infrastructure upgrades, migrations, and technology refresh activities.<br> Coordinate with Linux/OS, Storage, Network, Backup, and Cloud teams .<br> Maintain technical documentation and operational procedures.<br> Follow ITIL-based Incident, Problem, and Change Management processes.<br> Provide L2 support within a 24x7 managed services environment 8–12 years of experience in virtualization and Linux administration.<br> Strong hands-on experience with Oracle Linux KVM .<br> Strong knowledge of KVM and libvirt .<br> Experience managing enterprise production virtualization environments .<br> Hands-on experience with HA and live migration .<br> Strong knowledge of Oracle Linux / RHEL .<br> Experience supporting Production and DR environments .<br> Strong understanding of virtualization architecture and resource allocation.<br> Hands-on experience with: iSCSI NFS SAN Fibre Channel (FC) Strong understanding of virtual networking: VLAN Linux Bridges Bonding Experience with virtualization performance tuning and troubleshooting.<br> Experience with patching, upgrades, security hardening, and vulnerability remediation .<br> Basic scripting knowledge using Shell and/or Python .<br> Strong troubleshooting, analytical, and incident-management skills.<br> Familiarity with ITIL Incident, Problem, and Change Management .<br></span> </div>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <span></span><p><span>The production department is responsible for all the processes related to the manufacturing of the finished product batch starting with receiving and weighing the raw materials, bulk preparation, compression or encapsulation or liquid preparation and ending with the primary packaging, which is blistering, tablet or capsule filling or liquid filling. All processes are set to comply with current Good Manufacturing Processes.</span><br></p><br><p><span><b><span>Job Description</span></b><br></span></p><br><ol><li><span>Working with planning on prioritizing the monthly production plan based on machine capacity and lines productivity and based on planning department’s priorities to fulfill sales orders on time.</span><br></li></ol><ol><li><span>Continuously follow up on progress and adherence to the plan and report to the Production Director any delays and reasons for delays.</span><br></li></ol><br><ol><li><span>Review and assess the production processes and work flow to identify areas for improvement of process outputs and quality and to set a work plan for improvement.</span><br></li></ol><ol><li><span>Review the operating parameters of the machines and the set parameters and work to improve productivity in collaboration with Engineering department, technicians in production and machine operators.</span><br></li></ol><br><ol><li><span>Ensure employees’ commitment toward the approved work instructions, standard operating procedures and cGMP to ensure compliance is maintained during operations.Ensure compliance to the set documentation system.</span><br></li></ol><br><ol><li><span>Ensure that periodic maintenance of production machines and facilities are done on time and scheduled as part of the monthly plan.</span><br></li></ol><br><ol><li><span>Participate in process validation studies to ensure the validity of production’s methods, equipment and machines, review the validation protocols and reports and ensure that the process is planned to comply with the validated processes</span><br></li></ol><ol><li><span>Lead the trouble shooting activities and incidents and deviations investigations to address corrective and preventive actions leading to process improvements to reduce repeated problems and technical issues.</span><br></li></ol><br><ol><li><span>Ensure that overtime and shifts are managed with clear planning and follow up on progress and compliance to cGMP and SOPs and plan the shifts hours and overtime based on the production plan to reflect the actual need for that.</span><br></li></ol><br><ol><li><span>Ensure that the production employees are trained to perform their jobs and are trained on SOP’s.</span><br></li></ol><br><ol><li><span>Issue monthly production reports, quarter reports and annual production reports on time.&nbsp;</span><span>Monitor and evaluate the KPIs and provide feedback monthly to the production director.</span><br></li></ol><br><br><span>Requirements</span><p><b><span>Education:</span></b><br></p><br><p><span>BSc. degree in Pharmacy, Chemistry, Chemical or Industrial Engineering or any similar field.</span><br></p><br><p><b><span>Experience:</span></b><br></p><br><p><span>At least 15 years in the pharmaceutical manufacturing industry.</span><br></p><br><p><b><span>Skills required:</span></b><br></p><br><p><span><span>1.</span></span><span>Experience in management and industry improvement.</span><br></p><br><br><p><span><span>2.</span></span><span>Good knowledge in Quality Management systems and Good Manufacturing Practices.</span><br></p><br><p><span><span>3.</span></span><span>Strong problem solving and analytical skills</span><br></p><br><p><span><span>4.</span></span><span>Leadership and leading by example</span><br></p><br><p><span><span>5.</span></span><span>Good computer skills and strong report writing skills</span><br></p><br><p><span><span>6.</span></span><span>Multitasking</span><br></p><br><p><span><span>7.</span></span><span>Good communication skills.</span><br></p><br><br><br> </div>

<div> <p> <strong>POSITION SUMMARY</strong> </p> <p> </p> <p>Operate and monitor washing, dry cleaning, and drying machinery, including adding chemicals and cleaning lint traps. Identify stained or damaged items and determine status for repair, spot treatment, rewash, or discard. Inspect cleanliness of articles removed from the washer, dryer, or dry-cleaning machines and place in clean linen carts. Set dryers to designated times and temperatures based on fabrics contained in load. Remove lint and debris from dryer screens, dry cleaning filters, and drain trap after each load. Fold cleaned articles into designated size, either by hand or using folding machine. Maintain accurate records of items laundered.</p> <p> </p> <p>Follow all company safety and security policies and procedures; report accidents, injuries, and unsafe work conditions to manager; complete safety training and certifications. Follow all company policies and procedures; ensure uniform and personal appearance are clean and professional; maintain confidentiality of proprietary information; protect company assets. Develop and maintain positive working relationships with others; support team to reach common goals; listen and respond appropriately to the concerns of other employees. Ensure adherence to quality expectations and standards; identify, recommend, develop, and implement new ways to increase organizational efficiency, productivity, quality, safety, and/or cost-savings. Visually inspect tools, equipment, or machines (e.g., to identify defects). Stand, sit, or walk for an extended period of time or for an entire work shift. Move, lift, carry, push, pull, and place objects weighing less than or equal to 25 pounds without assistance. Move through narrow, confined, or elevated spaces. Move over sloping, uneven, or slippery surfaces as well as up and down stairs and/or service ramps. Reach overhead and below the knees, including bending, twisting, pulling, and stooping. Perform other reasonable job duties as requested by Supervisors.</p> <p> </p> <p>PREFERRED QUALIFICATIONS</p> <p>Education: No high school diploma or G.E.D. equivalent.</p> <p>Related Work Experience: No related work experience.</p> <p>Supervisory Experience: No supervisory experience.</p> <p>License or Certification: None</p> <p> </p> <p> </p> </div> <div> </div> <p><br></p>

<p>POSITION SUMMARY Operate and monitor washing, dry cleaning, and drying machinery, including adding chemicals and cleaning lint traps. Identify stained or damaged items and determine status for repair, spot treatment, rewash, or discard. Inspect cleanliness of articles removed from the washer, dryer, or dry-cleaning machines and place in clean linen carts. Set dryers to designated times and temperatures based on fabrics contained in load. Remove lint and debris from dryer screens, dry cleaning filters, and drain trap after each load. Fold cleaned articles into designated size, either by hand or using folding machine. Maintain accurate records of items laundered. Follow all company safety and security policies and procedures; report accidents, injuries, and unsafe work conditions to manager; complete safety training and certifications. Follow all company policies and procedures; ensure uniform and personal appearance are clean and professional; maintain confidentiality of proprietary information; protect company assets. Develop and maintain positive working relationships with others; support team to reach common goals; listen and respond appropriately to the concerns of other employees. Ensure adherence to quality expectations and standards; identify, recommend, develop, and implement new ways to increase organizational efficiency, productivity, quality, safety, and/or cost-savings. Visually inspect tools, equipment, or machines (e.g., to identify defects). Stand, sit, or walk for an extended period of time or for an entire work shift. Move, lift, carry, push, pull, and place objects weighing less than or equal to 25 pounds without assistance. Move through narrow, confined, or elevated spaces. Move over sloping, uneven, or slippery surfaces as well as up and down stairs and/or service ramps. Reach overhead and below the knees, including bending, twisting, pulling, and stooping. Perform other reasonable job duties as requested by Supervisors.</p><p><strong>Desired Candidate Profile</strong></p><p>Education: No high school diploma or G.E.D. equivalent. Related Work Experience: No related work experience. Supervisory Experience: No supervisory experience. License or Certification: None</p>

<p><h4>BlackStone eIT is actively looking for a dedicated AI team lead to spearhead our artificial intelligence initiatives.</h4> <p>This role involves leading a talented team of AI professionals to create innovative AI-driven solutions that align with the company's vision. You will play a crucial part in strategizing, developing, and deploying AI technologies that enhance our products and services while maintaining the highest standards of excellence.</p> <h4>Responsibilities:</h4> <ul> <li>Lead the AI team in designing, developing, and implementing AI models and systems.</li> <li>Collaborate with stakeholders to identify AI opportunities that drive business value.</li> <li>Guide the team to effectively use machine learning frameworks and tools.</li> <li>Oversee project lifecycle from research and prototyping to production deployment.</li> <li>Maintain knowledge of latest trends and advancements in AI and machine learning.</li> <li>Establish best practices and foster a culture of continuous improvement and innovation.</li> </ul> <h4>Requirements</h4> <ul> <li>Experience: 6+ years of hands-on experience in machine learning, deep learning, or AI engineering.</li> <li>3+ years of experience in a technical leadership or mentoring role.</li> <li>Programming & frameworks: Expert-level proficiency in Python and deep learning frameworks (PyTorch is strongly preferred, or TensorFlow).</li> <li>Cloud infrastructure: Extensive, hands-on experience with Microsoft Azure, specifically building training and deployment pipelines using Azure ML workspace, MLflow, and container orchestration (Docker/Kubernetes).</li> <li>NLP expertise: Deep understanding of modern NLP architectures (Transformers, BERT, GPT variants), tokenization, vector databases, and libraries like Hugging Face and Lang Chain/Lang Graph.</li> <li>CV expertise: Strong mathematical foundation in image processing and experience building custom models using OpenCV, YOLO architectures, and PyTorch Vision.</li> <li>MLOps: Proven ability to build CI/CD pipelines for machine learning models, manage model registries, and monitor model drift in production.</li> <li>Experience with building and deploying autonomous AI agents (e.g., using Langchain, Langgraph, Crew AI).</li> <li>Background in edge deployment for computer vision models (TensorRT, ONNX).</li> </ul> <h4>Benefits</h4> <ul> <li>Paid time off</li> <li>Performance bonus</li> <li>Training & development</li> </ul></p><p></p>

<p>We are looking for a Data Scientist &amp; Data QA Engineer to join our team to ensure the quality, reliability, and performance of our data, AI, and machine learning solutions. This role is ideal for someone who enjoys working with data, solving complex problems, automating quality checks, and improving the reliability of AI-driven products.</p><p><strong>Responsibilities:</strong></p><ul><li><strong>Data &amp; QA:</strong> Design and execute data quality checks; validate data for accuracy, completeness, and consistency; perform source-to-target validation and reconciliation; use SQL and Python to investigate anomalies; develop automated testing frameworks; and support regression testing for production data and ML solutions.</li><li><strong>AI &amp; Machine Learning:</strong> Evaluate AI/ML models against business requirements; analyze outputs for inconsistencies; and support testing for model performance, data drift, bias, and reliability alongside Data Scientists and ML Engineers.</li><li><strong>Generative AI, LLM &amp; RAG Validation:</strong> Support the quality of GenAI, LLM, and RAG applications; test responses for accuracy and factuality; identify hallucinations and bias; perform prompt and scenario-based testing; and develop test data for continuous quality monitoring.</li><li><strong>Collaboration:</strong> Partner with Data Scientists, Data, ML, and Software Engineers, and Product teams to define quality standards, test strategies, and acceptance criteria while performing root-cause analysis on defects.</li></ul><p><strong>Desired Candidate Profile</strong></p><ul><li>Bachelor's degree in Computer Science, Data Science, Engineering, or a related field.</li><li>Experience in one or more of the following: Data QA, Data Science, Data Engineering, Machine Learning, or AI/ML Testing.</li><li>Strong Python and SQL programming skills.</li><li>Experience with automated testing, preferably PyTest or similar frameworks.</li><li>Solid understanding of data quality concepts and machine learning fundamentals.</li><li>Strong knowledge of prompt engineering and experience designing and evaluating prompts for AI/LLM applications.</li><li>Working knowledge of MCP (Model Context Protocol) servers and how they integrate with AI/LLM applications.</li><li>Experience working with skills files / AI agent configuration and instruction files and understanding how they are used to guide AI workflows.</li><li>Hands-on experience with Claude Code or similar AI-assisted development tools.</li><li>Strong analytical, problem-solving, and communication skills.</li></ul><p><strong>Preferred Qualifications</strong></p><ul><li>Hands-on experience with Generative AI, LLM applications, RAG architecture, and AI evaluation frameworks such as Ragas, TruLens, or DeepEval .</li><li>Familiarity with LLM platforms such as OpenAI, Anthropic, and Llama , as well as concepts such as data/model drift and bias monitoring.</li><li>Experience with cloud platforms such as AWS, Azure, or GCP and CI/CD processes.</li></ul>

<p><br></p> <p> </p> <p> <strong>About the Role</strong> </p> <p>We are looking for a Data Scientist &amp; Data QA Engineer to join our team to ensure the quality, reliability, and performance of our data, AI, and machine learning solutions. This role is ideal for someone who enjoys working with data, solving complex problems, automating quality checks, and improving the reliability of AI-driven products.</p> <p> </p> <p> <strong>Responsibilities:</strong> </p> <ul> <li>Data &amp; QA: Design and execute data quality checks; validate data for accuracy, completeness, and consistency; perform source-to-target validation and reconciliation; use SQL and Python to investigate anomalies; develop automated testing frameworks; and support regression testing for production data and ML solutions.</li> <li>AI &amp; Machine Learning: Evaluate AI/ML models against business requirements; analyze outputs for inconsistencies; and support testing for model performance, data drift, bias, and reliability alongside Data Scientists and ML Engineers.</li> <li>Generative AI, LLM &amp; RAG Validation: Support the quality of GenAI, LLM, and RAG applications; test responses for accuracy and factuality; identify hallucinations and bias; perform prompt and scenario-based testing; and develop test data for continuous quality monitoring.</li> <li>Collaboration: Partner with Data Scientists, Data, ML, and Software Engineers, and Product teams to define quality standards, test strategies, and acceptance criteria while performing root-cause analysis on defects.</li> </ul> <p> </p> <p> <strong>Profile Requirements:</strong> </p> <ul> <li>Bachelor's degree in Computer Science, Data Science, Engineering, or a related field.</li> <li>Experience in one or more of the following: Data QA, Data Science, Data Engineering, Machine Learning, or AI/ML Testing.</li> <li>Strong Python and SQL programming skills.</li> <li>Experience with automated testing, preferably PyTest or similar frameworks.</li> <li>Solid understanding of data quality concepts and machine learning fundamentals.</li> <li>Strong knowledge of prompt engineering and experience designing and evaluating prompts for AI/LLM applications.</li> <li>Working knowledge of MCP (Model Context Protocol) servers and how they integrate with AI/LLM applications.</li> <li>Experience working with skills files / AI agent configuration and instruction files and understanding how they are used to guide AI workflows.</li> <li>Hands-on experience with Claude Code or similar AI-assisted development tools.</li> <li>Strong analytical, problem-solving, and communication skills.</li> <li>Preferred Qualifications</li> <li>Hands-on experience with Generative AI, LLM applications, RAG architecture, and AI evaluation frameworks such as <strong>Ragas, TruLens, or DeepEval</strong>.</li> <li>Familiarity with LLM platforms such as <strong>OpenAI, Anthropic, and Llama</strong>, as well as concepts such as data/model drift and bias monitoring.</li> <li>Experience with cloud platforms such as <strong>AWS, Azure, or GCP</strong> and CI/CD processes.</li> </ul> <p> </p> <p><br></p>

<p>POSITION SUMMARY Operate and monitor washing, dry cleaning, and drying machinery, including adding chemicals and cleaning lint traps. Identify stained or damaged items and determine status for repair, spot treatment, rewash, or discard. Inspect cleanliness of articles removed from the washer, dryer, or dry-cleaning machines and place in clean linen carts. Set dryers to designated times and temperatures based on fabrics contained in load. Remove lint and debris from dryer screens, dry cleaning filters, and drain trap after each load. Fold cleaned articles into designated size, either by hand or using folding machine. Maintain accurate records of items laundered. Follow all company safety and security policies and procedures; report accidents, injuries, and unsafe work conditions to manager; complete safety training and certifications. Follow all company policies and procedures; ensure uniform and personal appearance are clean and professional; maintain confidentiality of proprietary information; protect company assets. Develop and maintain positive working relationships with others; support team to reach common goals; listen and respond appropriately to the concerns of other employees. Ensure adherence to quality expectations and standards; identify, recommend, develop, and implement new ways to increase organizational efficiency, productivity, quality, safety, and/or cost-savings. Visually inspect tools, equipment, or machines (e.g., to identify defects). Stand, sit, or walk for an extended period of time or for an entire work shift. Move, lift, carry, push, pull, and place objects weighing less than or equal to 25 pounds without assistance. Move through narrow, confined, or elevated spaces. Move over sloping, uneven, or slippery surfaces as well as up and down stairs and/or service ramps. Reach overhead and below the knees, including bending, twisting, pulling, and stooping. Perform other reasonable job duties as requested by Supervisors.</p><p><strong>Desired Candidate Profile</strong></p><p>Education: No high school diploma or G.E.D. equivalent.<br>Related Work Experience: No related work experience.<br>Supervisory Experience: No supervisory experience.<br>License or Certification: None</p>