Microsoft Logo

Microsoft

Capacity & Efficiency Infrastructure

Posted 7 Hours Ago
Be an Early Applicant
Remote
Hiring Remotely in United States
120K-304K Annually
Senior level
Remote
Hiring Remotely in United States
120K-304K Annually
Senior level
Design, implement, and optimize large-scale distributed training infrastructure and telemetry for GPU clusters. Profile, benchmark, and debug performance across compute, memory, networking, and storage. Improve collective communication libraries and collaborate with ML researchers and hardware teams to scale models, optimize accelerators, and deliver fleet-wide efficiency improvements and automated recommendations.
The summary above was generated by AI
Overview

Microsoft AI is looking for a Member of Technical Staff – Capacity & Efficiency Infrastructure, to help us improve manage, and improve the efficiency of, our compute fleet. We’re seeking someone who brings an abundance of positive energy, empathy, and kindness to the team every day, in addition to being highly effective. The ideal candidate enjoys building world-class consumer experiences and products in a fast-paced environment. You will actively contribute to the development of AI models powering our innovative products. Expect to wear multiple hats and work across engineering, research, and everything in between. Your contributions will span model architecture, data curation, training and inference infrastructure, evaluation protocols, alignment and reinforcement learning from human feedback (RLHF), and many other exciting topics at the cutting edge of AI.

Microsoft AI is building the training infrastructure that powers frontier-scale models and advances research toward humanist superintelligence.


As a Member of Technical Staff – Capacity & Efficiency, you will contribute to a fast-moving codebase that enables training at an unprecedented scale. This role will require building software and mathematical models for measuring the effectiveness of our capacity usage and then developing tools and techniques to help us improve. This will require you to partner with ML researchers to scale up the latest research recipes, implement new forms of distributed training parallelism, and ensure the reliability and performance of thousands of GPUs across our supercomputing fleet. Profiling, benchmarking, debugging, and fine-grained optimization are core to this role, demanding both engineering rigor and creativity.


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, implement, test, and optimize distributed training infrastructure in Python and C++ for large-scale GPU clusters.
  • Build and evolve telemetry systems to provide visibility into infrastructure & ML model performance, utilization, and cost related metrics
  • Profile, benchmark, and debug performance bottlenecks across compute, memory, networking, and storage subsystems
  • Drive architectural improvements across various ML services which deliver measurable efficiency improvements
  • Build and evolve tools to automatically provide insights and recommendations to improve fleet-wide efficiency
  • Optimize collective communication libraries (e.g., NCCL) for emerging NVLink and InfiniBand topologies
  • Partner with ML researchers and infrastructure engineers to understand their plans and future needs and develop plans to balance growth with efficiency
  • Collaborate with hardware teams to optimize for next-generation accelerators (NVIDIA, MAIA, and beyond)
  • Embody our Culture and Values.

Qualifications

Required Qualifications:

  • Bachelor’s Degree in Computer Science, or related technical discipline AND 6+ 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:

  • Bachelor’s Degree in Computer Science or related technical field AND 10+ years technical engineering experience with coding in languages including, but not limited to,  C++ or Python OR Master’s Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C++  or Python
    • OR equivalent experience
  • Deep understanding of the fundamentals of GPU architectures and DL/LLM architectures
  • Deep experience in profiling and analyzing performance in large-scale distributed computing systems.
  • Deep experience in profiling and analyzing performance in ML models especially GenAI models
  • Experience with low-level GPU programming (CUDA, Triton, NCCL) and frameworks such as PyTorch or JAX.
  • Experience in leading technical projects and supporting architectural decisions with data.  
  • Experience building infrastructure for large-scale machine learning or generative AI workloads.
  • Experience in networking (InfiniBand, NVLink), storage systems, or distributed training parallelisms.
  • Track record of contributing to high-performance computing or large-scale AI infrastructure projects.

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

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


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.

Similar Jobs

17 Minutes Ago
Remote
USA
50K-55K Annually
Entry level
50K-55K Annually
Entry level
Fintech • Mobile • Real Estate • Financial Services • PropTech
Serve as first-line member support via chat and ticketing, resolving entry-level issues (payments, loyalty), triaging and escalating complex cases, documenting interactions, collaborating with internal teams and BPO partners, staying current on product changes, and delivering patient, organized digital customer service.
22 Minutes Ago
Remote or Hybrid
120K-155K Annually
Senior level
120K-155K Annually
Senior level
Artificial Intelligence • Big Data • Cloud • Information Technology • Software • Big Data Analytics • Automation
Senior BI Platform Administrator to own enterprise BI infrastructure across Power BI, Microsoft Fabric, and Snowflake. Responsibilities include federated Power BI governance, Fabric AI Agent skill design and deployment, RBAC/RLS design, certified semantic model development, CI/CD and SRE practices for platform reliability, and measuring adoption. Partners with Data Engineering, IT Security, AI/ML, and business stakeholders to drive secure, performant analytics and AI-powered experiences.
Top Skills: Azure DevopsAzure MonitorCopilot StudioCortex SearchCube.DevDaxDbtDirectqueryFabric Ai Agent SkillsFabric GitLakehouseLog AnalyticsMicrosoft FabricPower AutomatePower BIPower Bi Rest ApiPower Query MRbacRow-Level SecuritySemantic ViewsSnowflakeSnowflake CortexSQL
24 Minutes Ago
Easy Apply
Remote or Hybrid
United States
Easy Apply
101K-136K Annually
Senior level
101K-136K Annually
Senior level
Artificial Intelligence • Cloud • Computer Vision • Hardware • Internet of Things • Software
Lead positioning and sale of Samsara Professional Services during the sales cycle: scope engagements, produce SOWs and proposals, forecast and hit ARR attach quota, coordinate transitions to Customer Success, advise executives during implementation, and help build services methodologies and collateral.
Top Skills: Internet Of Things (Iot)Salesforce (Sfdc)

What you need to know about the NYC Tech Scene

As the undisputed financial capital of the world, New York City is an epicenter of startup funding activity. The city has a thriving fintech scene and is a major player in verticals ranging from AI to biotech, cybersecurity and digital media. It also has universities like NYU, Columbia and Cornell Tech attracting students and researchers from across the globe, providing the ecosystem with a constant influx of world-class talent. And its East Coast location and three international airports make it a perfect spot for European companies establishing a foothold in the United States.

Key Facts About NYC Tech

  • Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
  • Key Industries: Artificial intelligence, Fintech
  • Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
  • Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account