ML Engineer

Microsoft • Redmond, WA

3d • Onsite

About The Position

You’ll help build core generative AI and multimodal capabilities that power customer-facing AI services at global scale. In this role, you’ll combine software engineering with applied ML expertise to design, ship, and operate production systems—using techniques like context engineering, synthetic data generation, and rigorous evaluation/metrics to continuously improve quality. You’ll collaborate closely across product, research, and service engineering to deliver secure, performant improvements for enterprise customers.
This position is in-office, with a minimum of 3 days/week in office.
Microsoft’s mission is to empower every person and every organization on the planet to achieve more, and we’re dedicated to this mission across every aspect of our company. Our culture is centered on embracing a growth mindset and encouraging teams and leaders toperform at a high level each day. Join us and help shape the future of the world.

Requirements

• Bachelor's Degree in Computer Science or related technical field AND 2+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.
• Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include, but are not limited to the following specialized security screenings: Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.

Nice To Haves

• 3+ years of experience in software engineering, machine learning engineering, or applied AI (or equivalent experience).
• Experience contributing to technical designs and delivering features in complex codebases (e.g., writing design docs, reviewing changes, and improving reliability/performance).
• Experience building and shipping generative AI systems (including multimodal scenarios).
• Experience building and operating ML/AI systems in cloud environments; familiarity with MLOps practices (Azure a plus).
• Experience partnering with cross-functional stakeholders to define requirements and drive technical decisions.
• Advanced degree in Computer Science, Machine Learning, or related field.
• Experience with prompt engineering, retrieval-augmented generation (RAG), and memory/agent frameworks.
• Familiarity with compliance and security standards in enterprise AI solutions.
• Track record of delivering enterprise-facing AI products at scale.

Responsibilities

• Design, build, and operate production-grade generative AI and multimodal systems, with ownership from implementation through deployment and live-site operations.
• Contribute to the design and implementation of core GenAI capabilities (e.g., retrieval-augmented generation, context and memory, orchestration) and make data-driven tradeoffs across quality, latency, cost, and safety.
• Improve model and system quality using evaluation frameworks, experiment design, and production telemetry; build robust testing, monitoring, and regression coverage.
• Work with security, privacy, and compliance partners to build solutions that meet enterprise requirements and align with Responsible AI standards and practices.
• Collaborate with teammates through design reviews, code reviews, and debugging to unblock delivery and improve architecture, code quality, and ML engineering practices.
• Partner with product and customers to understand scenarios, translate requirements into well-designed APIs and developer experiences, and contribute to adoption through documentation and samples.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level