Senior Machine Learning Engineer

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

• Architect and productionize AI systems that power risk scoring, classifier-level reasoning, explainability narratives, and intelligent recommendations across multi-tenant SaaS environments.
• Design and build GenAI pipelines (RAG + agentic orchestration) including indexing, embedding strategies, retrieval optimization, prompt frameworks, tool integration, and memory/control flows tailored for security use cases.
• Own model evaluation and guardrails, defining offline/online metrics (precision, recall, risk calibration, hallucination control), building evaluation harnesses, and implementing responsible AI safeguards.
• Optimize model trade-offs (latency, cost, accuracy, safety) and deploy scalable inference systems with monitoring, drift detection, and feedback loops from customer signals.
• Partner with Product and Engineering to translate ambiguous security requirements into reliable AI-native workflows that are simple, trustworthy, and adoption-ready for SMB/SMC and Enterprise customers.

• 8+ years of experience building and deploying machine learning systems in production environments.
• Strong hands-on experience with LLMs, RAG architectures, and applied Generative AI systems, including prompt design and grounding techniques.
Proven expertise in designing end-to-end ML pipelines (data ingestion feature engineering training evaluation
• serving).
• Experience defining and operationalizing offline and online evaluation frameworks (precision/recall, calibration, drift detection, A/B testing) and implementing guardrails for reliability and safety.
• Strong programming skills in Python, with experience in modern ML frameworks (e.g., PyTorch/TensorFlow) and cloud-based ML infrastructure; experience building multi-tenant SaaS AI systems with attention to scalability, latency, and cost optimization.
• Experience fine-tuning or adapting foundation models (e.g., LoRA/PEFT) and building agentic orchestration systems is preferred; knowledge of data security, compliance, or risk-scoring domains will be an additional advantage.

This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process.