Overview

Are you a customer-obsessed, AI-curious problem-solver who thrives in an inclusive, collaborative global team? Join Engineering Operations (EngOps) – the organization driving operational excellence across the Microsoft Cloud to strengthen quality, reliability, security, and customer trust. As part of EngOps, you’ll design solutions that prevent issues before they happen, embed AI-powered automation, and turn signals into actions that deliver measurable customer impact. Our culture of empowerment, inclusion, and growth mindset defines how we work.

Azure Reliability is driving transformation to AI-powered operations by building scalable ML infrastructure that enables autonomous, reliable, and secure cloud systems. We are looking for candidates that can combine deep technical expertise in MLOps with a proven ability to deliver measurable business impact through continuous learning, policy-driven governance, and responsible AI practices. Success in this role means advancing operational autonomy, quality, and security, while fostering collaboration and accountability across teams.

Every day, customers stake their business and reputation on our cloud. You can help #EngOps keep them secure, resilient, and ready.

This role will require a minimum of three days in office.

Company Culture Statement

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.

Responsibilities

Responsibilities:

Design and implement robust ML pipelines for training, deployment, and monitoring
Build feature stores and reusable ML components for cross-team use
Develop frameworks for data validation, drift detection, and auditability
Ensure compliance with data privacy regulations and ethical standards Optimize models for performance, cost-efficiency, and scalability
Partner with product and business teams to identify high-value ML use cases

Qualifications

Bachelor's Degree in Computer Science, or related technical discipline AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python or equivalent experience.

Preferred Qualifications

Strong proficiency in machine learning algorithms, deep learning frameworks (e.g., PyTorch, TensorFlow), and data science fundamentals
Experience with MLOps tools and practices (CI/CD for ML, model monitoring, automated retraining)
Solid understanding of cloud platforms (Azure, AWS, GCP) and distributed systems for large-scale ML
Expertise in data pipeline design, feature stores, and data validation frameworks
Hands-on experience with LLM fine-tuning, retrieval-augmented generation (RAG), and embedding optimization
5–8 years in ML engineering or applied AI roles, with proven track record of production-grade deployments

Software Engineering IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $158,400 - $258,000 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay

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.

Senior Software Engineering