Senior Software Engineer -ai/ml

Microsoft Microsoft · Big Tech · Hyderabad, TS, IN · Software Engineering

Senior Software Engineer focused on building and scaling AI/ML-powered features for Windows, integrating multimodal input, agentic workflows, and generative AI. The role involves end-to-end development, from research and implementation of foundation models, prompt engineering, RAG, and multi-agent architectures, to fine-tuning, evaluation, and production deployment. Emphasis on creating inclusive and accessible experiences, particularly for users with disabilities, using human-centered AI.

What you'd actually do

  1. Build collaborative relationships with product and business groups to deliver Al-driven impact
  2. Research and implement state-of-the-art using foundation models, prompt engineering, RAG, graphs, multi-agent architectures, as well as classical machine learning techniques.
  3. Fine-tune foundation models using domain-specific datasets.
  4. Evaluate model behavior on relevance, bias, hallucination, and response quality via offline evaluations, shadow experiments, online experiments, and ROI analysis.
  5. Build rapid Al solution prototypes, contribute to production deployment of these solutions, debug production code, support MLOps/AIOps.

Skills

Required

  • Bachelor's Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java or Python.
  • 4+ Overall experience End- end shipping of commercial software, with at least 3+ years of experience in AI/ML, predictive analytics or research, and exposure to generative AI/LLM/SLM algorithms.
  • Customer focused innovation mindset.
  • Passion for Craftmanship in engineering.
  • Deep expertise in Al subfields (e.g., deep learning, Generative Al, NLP, muti- modal models)

Nice to have

  • Experience with cross group design and coordination is an advantage.

What the JD emphasized

  • end-to-end shipping of commercial software
  • AI/ML, predictive analytics or research
  • generative AI/LLM/SLM algorithms
  • building reliable, well-documented research code that drives rapid experimentation, scalable evaluation, and efficient deployment from prototype to production in applied Al research.

Other signals

  • building and scaling intelligent experiences
  • integrating multimodal input, agentic workflows, and generative AI
  • delivering high-impact features
  • implementing state-of-the-art using foundation models, prompt engineering, RAG, graphs, multi-agent architectures
  • fine-tune foundation models
  • evaluate model behavior
  • translate research into production-ready solutions