Senior AI or ML Engineer - Azure, Python, GenAI
Indexed description
Primary Responsibilities
- Design, build, and maintain production-quality Python services supporting ML and GenAI workflows (data preparation, training, evaluation, inference)
- Develop and deploy AI/ML solutions using Azure Machine Learning, including experiments, pipelines, model registration, and endpoints
- Design and implement Generative AI solutions, including LLM-based applications and Retrieval-Augmented Generation (RAG) patterns
- Lead model packaging, versioning, and deployment to secure, scalable endpoints
- Apply and evolve MLOps best practices, including CI/CD, automation, monitoring, reproducibility, and documentation
- Collaborate with data engineering, platform, and DevOps teams to integrate ML solutions into broader systems
- Review code, mentor junior engineers, and contribute to team standards and technical direction
- Communicate technical designs, tradeoffs, and results clearly to both engineering and non-engineering stakeholders
- Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so
- Graduate degree or equivalent experience
- Bachelor's or Master's degree in Computer Science, Software Engineering, Data Science, or a related field - or equivalent practical experience
- 5+ years of professional software engineering experience, with hands-on AI/ML development in production environments
- Experience using Git, pull requests, and collaborative development workflows
- Practical experience designing and implementing RAG architectures and working with LLMs / GenAI frameworks
- Solid understanding of machine learning fundamentals, including training/evaluation workflows, metrics, and common algorithms
- Familiarity with AI-assisted development tools (e.g., GitHub Copilot) and how to use them effectively in day-to-day engineering work
- Solid proficiency in Python, with experience building maintainable, testable, and scalable systems
- Hands-on experience with Azure Machine Learning (workspaces, compute, pipelines, jobs, and endpoints)
- Experience deploying and operating LLM-powered services at scale
- Experience mentoring engineers or providing technical leadership on AI/ML initiatives
- Experience working on at least one major cloud platform, with hands-on Azure experience Solid understanding of MLOps concepts such as CI/CD, monitoring, model governance, and reproducibility
- Background in designing secure, compliant AI systems in enterprise environments
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