Role intent Live

Senior Machine Learning Engineer

Microsoft

Work Mode

Onsite

Employment Type

FULL TIME

Location

India, Telangana, Hyderabad, India, Uttar Pradesh, Noida

Application Deadline

September 19, 2026

Design, develop, and deploy AI / ML systems across the full lifecycle, including data ingestion, feature engineering, model training, evaluation, and production integration. Ship and operate large‑scale AI services in cloud environments, with ownership of reliability, latency, throughput, accuracy, and cost efficiency. Apply Responsible AI principles—privacy, security, explainability, fairness, and compliance—throughout system design and deployment. Stay current with advancements in GenAI, LLM f…

Responsibilities

Build and optimize Generative AI and LLM‑based systems, including agentic workflows, prompt engineering, retrieval‑augmented generation (RAG), and fine‑tuning approaches. Write production‑grade code (Python, C#, and/or Java) with a strong focus on scalability, performance, security, testability, and maintainability. Partner closely with engineering, product management, and applied science teams to translate business and customer requirements into robust technical solutions. Define and execute model evaluation strategies, including offline experiments, online monitoring, drift detection, bias analysis, and feedback loops. Implement MLOps best practices, including CI/CD for models, versioning, rollout strategies, observability, and live‑site monitoring. Contribute technical leadership by reviewing designs, mentoring peers, and raising the overall engineering and scientific bar of the team.

Required Qualifications

Bachelor's degree in Computer Science, Data Science, Engineering, or a related technical field. 7+ years of overall experience, including 5+ years of hands‑on software engineering experience writing production‑quality code and 3+ years designing and implementing end‑to‑end software systems. Solid understanding of machine learning fundamentals, model evaluation, experimentation, and performance trade‑offs and experience building or operationalizing LLM / Generative AI systems, including RAG, prompt engineering, or agent‑based architectures. Proven ability to collaborate across disciplines and operate with autonomy at senior IC scope.

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