Machine Learning Engineer II at Microsoft

, , India -

Full Time

Start Date

Immediate

Expiry Date

10 Apr, 26

Salary

0.0

Posted On

10 Jan, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Artificial Intelligence, Deep Learning, Natural Language Processing, Large Language Models, Reinforcement Learning, Graph-Based Approaches, Python, C#, Java, Generative AI, MLOps, Model Evaluation, Feature Engineering, Cloud Environments, Responsible AI

Industry

Software Development

Description

Overview Microsoft Security represents one of the company’s most critical priorities—protecting customers in an era of increasing digital threats, regulatory scrutiny, and expanding cloud complexity. Our mission is to make the world safer by empowering organizations with intelligent, simplified, and trusted security solutions. The Purview team is at the forefront of applying Artificial Intelligence—including deep learning, natural language processing, large language models (LLMs), reinforcement learning, and graph‑based approaches—to solve complex data security and compliance challenges. We focus on translating cutting‑edge research into scalable, production‑ready AI systems that deliver real customer impact today while preparing for future threats. We are seeking a ML Engineer/ Machine Learning Engineer to join a Group Squad within Purview. In this role, you will design, build, and operate AI‑driven solutions—from experimentation to large‑scale deployment—working closely with software engineers, product managers, and data scientists. You will bring strong engineering judgment, scientific rigor, and a customer‑first mindset to deliver secure, reliable, and responsible AI systems at Microsoft scale. Microsoft is a growth‑mindset organization. We value respect, integrity, accountability, and inclusion, enabling every employee to thrive while building technology that changes lives. Responsibilities Design, develop, and deploy AI / ML systems across the full lifecycle, including data ingestion, feature engineering, model training, evaluation, and production integration. 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. Ship and operate large‑scale AI services in cloud environments, with ownership of reliability, latency, throughput, accuracy, and cost efficiency. 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. Apply Responsible AI principles—privacy, security, explainability, fairness, and compliance—throughout system design and deployment. Stay current with advancements in GenAI, LLM frameworks, and ML infrastructure, assessing feasibility and impact for enterprise security scenarios. Contribute technical leadership by reviewing designs, mentoring peers, and raising the overall engineering and scientific bar of the team. Qualifications Bachelor’s degree in Computer Science, Data Science, Engineering, or a related technical field. 3+ years of overall experience, including: 2+ years of hands‑on software engineering experience writing production‑quality code. 2+ years designing and implementing end‑to‑end software systems. 2+ years shipping and operating large‑scale ML or AI services in cloud environments (Azure, AWS, or GCP). Strong proficiency in Python and at least one of C# or Java. Solid understanding of machine learning fundamentals, model evaluation, experimentation, and performance trade‑offs. 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. Preferred Qualifications Master’s or PhD in Machine Learning, AI, Computer Science, or a related field. Experience working on security, compliance, or privacy‑sensitive systems. Deep familiarity with Azure ML, data platforms, or large‑scale distributed systems. Experience applying Responsible AI principles in regulated or enterprise environments. 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, read more about requesting accommodations.

Responsibilities

Design, develop, and deploy AI/ML systems across the full lifecycle, including data ingestion and model training. Collaborate with engineering and product teams to translate requirements into technical solutions.