Principal Machine Learning Engineer

Microsoft•Redmond, WA

81d

About The Position

Core AI is at the forefront of Microsoft’s mission to redefine how software is built and experienced. We are responsible for building the foundational platforms, services, programming models, and developer experiences that power the next generation of applications using Generative AI. Our work enables developers and enterprises to harness the full potential of AI to create intelligent, adaptive, and transformative software. The Observability group is focused on developing solutions to monitor, evaluate, and optimize AI agent performance. We are seeking a passionate and skilled software engineer to join the Observability platform team. This team is responsible for building the services that power Observability in Foundry.

Requirements

Bachelor's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C++, C#, Go, Java, 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

8+ years of technical engineering experience with coding in languages including, but not limited to, C++, C#, Go, Java, or Python
3+ years of technical engineering experience with machine learning or AI systems
Experience building or maintaining evaluation systems, benchmarking tools, or ML model testing frameworks.
ML, statistics, and data science experience are a plus
6+ years technical engineering experience designing and delivering highly available, large-scale cloud services and distributed systems.
Experience building AI or ML related applications.

Responsibilities

Design, implement and deliver AI services to support product offerings for large-scale agent observability
Design and build the end-to-end pipelines covering model training, data analysis, model serving and model evaluation.
Design and develop scalable systems for benchmarking AI models, including pipelines for automated evaluation, metric tracking, and result visualization.
Build and maintain a robust data platform to support model evaluation workflows, including ingestion, versioning, and storage of datasets and model artifacts.
Demonstrate good understanding of LLM architectures, training and inference
Collaborate closely with product management and partner teams to align technical direction with business goals
Take end-to-end responsibility for the development lifecycle and production readiness of the services you build and drive the team’s DevOps culture
Engage with customers to gather feedback and resolve complex issues
Understand Microsoft businesses and collaborate with stakeholders towards cohesive, end-to-end experiences for Microsoft customers
Innovate on technical solutions, and patterns that will improve the availability, reliability, efficiency, observability, and performance of products.