High Performance Computing Engineer

Reposted Yesterday
Be an Early Applicant
Hiring Remotely in United States
Remote
120K-304K Annually
Mid level
Software • Quantum Computing • Metaverse • Infrastructure as a Service (IaaS)
The Role
Design, deploy, operate, and tune large-scale HPC environments for AI model training. Own HPC domains (GPU compute, storage, networking), manage schedulers (SLURM, Kubernetes), build automation in Bash/Python, troubleshoot cluster performance, and partner with researchers to support high-scale training workloads.
Summary Generated by Built In
Overview

Microsoft AI is looking for experienced Member of Technical Staff, High Performance Computing Engineers to help build and scale the infrastructure that trains our frontier models and powers the next evolution of our personal AI, Copilot. This role offers the unique opportunity to work on some of the largest scale supercomputers in the world - a rare chance to operate at such a significant scale. 

Microsoft AI
This role is part of Microsoft AI. Our Superintelligence team is a startup-like organization within Microsoft, dedicated to pushing the boundaries of artificial intelligence while maintaining a strong commitment to safety, responsibility, and human values.
Our mission is to build AI that amplifies human potential and empowers people around the world. We strive to deliver breakthroughs that advance science, education, productivity, and global well-being.
Thank you!
We’re also fortunate to partner with incredible product teams giving our models the chance to reach billions of users and create immense positive impact. If you’re a brilliant, highly-ambitious and low ego individual, you’ll fit right in—come and join us as we work on our next generation of models!

Starting January 26, 2026, MAI employees are expected to work from a designated Microsoft office at least four days a week if they live within 50 miles (U.S.) or 25 miles (non-U.S., country-specific) of that location. This expectation is subject to local law and may vary by jurisdiction.




Responsibilities
  • Design, operate, and maintain large-scale HPC environments, drawing on hands-on engineering experience in production settings.
  • Own the deployment, configuration, and day-to-day operation of HPC schedulers (e.g., SLURM, Kubernetes), ensuring reliable and efficient job scheduling at scale.
  • Serve as a technical owner for at least one core HPC domain (GPU compute, high-performance storage, networking, or similar), including ongoing maintenance, performance tuning, and troubleshooting of massive clusters.
  • Develop and maintain automation and tooling using Bash and/or Python to improve cluster reliability, observability, and operational efficiency.
  • Partner closely with researchers and engineers to support their workloads, troubleshoot cluster usage issues, and triage failed or underperforming jobs to resolution.
  • Drive work forward independently by navigating ambiguity and technical roadblocks, delivering incremental improvements that get capabilities into users’ hands quickly.
  • Enjoy working in a fast-paced, design-driven product development environment, balancing stability with rapid iteration and experimentation.
  • Embody our Culture and Values.  

Qualifications

Required Qualifications:

  • Do you have a Bachelor’s degree in computer science, or related technical field AND 4+ years technical engineering experience with deploying or operating on-premise or cloud high-performance clusters, AND 4+ years experience working with high-scale training clusters (ex. working with frameworks/tools such as nvidia InfiniBand clusters, SLURM, Kubernetes, Ray, etc.), AND 4+ years experience building scalable services on top of public cloud infrastructure like Azure, AWS, or GCP,
    • OR equivalent experience? 

Preferred Qualifications:

  • Master's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with deploying or operating on-premise or cloud high-performance clusters, AND 6+ years experience working with high-scale training clusters (ex. working with frameworks/tools such as nvidia InfiniBand clusters, SLURM, Kubernetes, Ray, etc.), AND 6+ years experience building scalable services on top of public cloud infrastructure like Azure, AWS, or GCP,
    • OR equivalent experience.
  • Experience with LLM training clusters
  • Experience working with AI platforms, frameworks, and APIs
  • Experience using Machine Learning frameworks, including experience using, deploying, and scaling language learning models, either personally or professionally.
  • Experience working with large-scale HPC or GPU systems (ex. NVIDIA H100/GB200 or equivalent).
  • Ability to identify, analyze, and resolve complex technical issues, ensuring optimal performance, scalability, and user experience.
  • Dedication to writing clean, maintainable, and well-documented code with a focus on application quality, performance, and security.
  • Demonstrated interpersonal skills and ability to work closely with cross-functional teams, including product managers, designers, and other engineers.
  • Ability to clearly communicate complex technical concepts to both technical and non-technical stakeholders.
  • Passion for learning new technologies and staying up to date with industry trends, best practices, and emerging technologies.
  • Ability to work in a fast-paced environment, manage multiple priorities, and adapt to changing requirements and deadlines.
  • Proven ability to collaborate and contribute to a positive, inclusive work environment, fostering knowledge sharing and growth within the team. 

Software Engineering IC5 - The typical base pay range for this role across the U.S. is USD $142,800 - $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

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 $160,200 - $261,000 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.

Skills Required

  • Bachelor's degree in computer science or related technical field OR equivalent experience
  • 4+ years technical engineering experience deploying or operating on-premise or cloud high-performance clusters
  • 4+ years experience working with high-scale training clusters (e.g., NVIDIA InfiniBand clusters, SLURM, Kubernetes, Ray)
  • 4+ years experience building scalable services on public cloud infrastructure (Azure, AWS, or GCP)
  • Develop and maintain automation and tooling using Bash and/or Python
  • Master's degree in Computer Science or related field OR 6+ years equivalent experience (preferred alternative)
  • Experience with LLM training clusters
  • Experience working with AI platforms, frameworks, and APIs
  • Experience using, deploying, and scaling machine learning frameworks and language models
  • Experience with large-scale GPU systems (e.g., NVIDIA H100/GB200)
  • Strong troubleshooting, communication, collaboration, and ability to work in fast-paced environments

Microsoft Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Microsoft and has not been reviewed or approved by Microsoft.

  • Fair & Transparent Compensation Pay is presented as broadly competitive overall, with clear role/level/location variation and an emphasis on using posted ranges and band information for apples-to-apples comparisons.
  • Retirement Support Retirement benefits are described as a standout, highlighted by a strong 401(k) match structure and immediate vesting, plus additional plan features for tax-advantaged saving.
  • Parental & Family Support Family-oriented benefits are portrayed as a meaningful strength, with substantial paid parental leave and added supports like back-up care and adoption/surrogacy assistance.

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