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Job Details
Posted date: Jul 14, 2025
There have been 2 jobs posted with the title of Principal Machine Learning Engineer - CoreAI all time at Microsoft.There have been 2 Principal Machine Learning Engineer - CoreAI jobs posted in the last month.
Category: Research, Applied, & Data Sciences
Location: Redmond, WA
Estimated salary: $222,050
Range: $139,900 - $304,200
Employment type: Full-Time
Travel amount: 25.0%
Work location type: Microsoft on-site only
Role: Individual Contributor
Description
The Microsoft CoreAI Post-Training team is dedicated to advancing post-training methods for both OpenAI and open-source models. Their work encompasses continual pre-training, large-scale deep reinforcement learning running on extensive GPU resources, and significant efforts to curate and synthesize training data. In addition, the team employs various fine-tuning approaches to support both research and product development.The team also develops advanced AI technologies that integrate language and multi-modality for a range of Microsoft products. The team is particularly active in developing code-specific models, including those used in Github Copilot and Visual Studio Code, such as code completion model and the software engineering (SWE) agent models.
The team has also produced publications as by-products, including work such as LoRA, DeBerTa, Oscar, Rho-1, Florence, and the open-source Phi models.
We are looking for a Principal Machine Learning Engineer - CoreAI with significant experience in large-scale model deployment, production systems, and engineering excellence, ideally from leading technology companies. You will build and optimize production systems for LLMs, SLMs, multimodal, and coding models using both proprietary and open-source frameworks. Key responsibilities include ensuring model reliability, inference performance, and scalability in production environments, and managing the full engineering pipeline from model training, serving, monitoring, to continuous deployment.
Our team values startup-style efficiency and practical problem-solving. We are seeking a curious, adaptable problem-solver who thrives on continuous learning, embraces changing priorities, and is motivated by creating meaningful impact. Candidates must be self-driven, able to write production-grade code and debug complex distributed systems, document engineering decisions, and demonstrate a track record in shipping ML systems at scale. The ability to quickly translate ideas into working code for rapid experimentation would be a plus. You may include information about any individual who can serve as your referral in your application.
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.
In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positively impact our culture every day.
Core Qualifications & Responsibilities
Design and implement large-scale model training - Especially with LLMs, SLMs, multimodal, or code-specific models. System optimization and performance - Optimize inference latency, throughput, and resource utilization for training and inference workloads. Hands-on coding- Ability to write efficient, production-quality code and debug complex distributed systems. Cross-platform integration - Work with both proprietary and open-source frameworks to build robust ML pipelines. Production model deployment - Design and implement scalable serving infrastructure for LLMs, SLMs, multimodal, and code-specific models. Research & Innovation
Contribute to or build on existing innovations like technical report of the well-known models. Develop novel AI solutions that bridge language, vision, and code understanding. Help develop models powering tools like GitHub Copilot, Cursor, and VS Code suggestions. Other:
Embody our Culture and Values
Qualifications
Required/Minimum QualificationsDoctorate in relevant field AND 3+ years related research experience OR equivalent experience3+ years of coding experience in Python and experience with ML frameworks such as PyTorch and Triton3+ years of proven ability to design and scale training infrastructure and pipelines in production environments3+ years of experience in production ML systems, especially on finetuning LLMs, SLMs, multimodal, or code-specific models3+ years of expertise in system architecture and scalability, designing and implementing large-scale distributed systems, such as batching, caching, load balancing, and model parallelism3+ years of proficiency in building and maintaining ML production pipelinesOther Requirements:
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.Preferred/Additional Qualifications
Proven track record of shipping generative AI products, preferably at leading technology companies, with demonstrated impact on production systemsExtensive experience with generative AI infrastructure, including model training, inference, quantization, deployment, and performance optimization for foundation modelsHands-on experience with large-scale distributed systems - systems thinking and experience with high-availability, low-latency inference servicesProficiency in containerization (Docker / Kubernetes)Experience with MLOps and DevOps practices, CI/CD pipelines, automated testing, deployment strategies, and infrastructure as codeDemonstrated ability to work in cross-functional teams and collaborate effectively with researchers, product managers, and other engineers to deliver complex ML solutionsLeadership and influence with the ability to lead projects and influence others across teams and disciplinesAI-forward approach with a demonstrated willingness to incorporate AI tools in day-to-day work to enhance productivity and innovation Self-driven and organized with the ability to take ownership of projects and document findings clearly and effectivelyStartup-style mindset - agile, solution-oriented, and able to operate with minimal overhead
Research Sciences IC5 - The typical base pay range for this role across the U.S. is USD $139,900 - $274,800 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 $188,000 - $304,200 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
Microsoft posts positions for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
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