header alt image test
Microloft Logo

Microloft

Software Engineer - Compute Infra / HPC

Reposted 3 Days Ago
Be an Early Applicant
Remote
Hiring Remotely in United States
120K-304K Annually
Mid level
Remote
Hiring Remotely in United States
120K-304K Annually
Mid level
Design, operate, and maintain large-scale HPC environments for training frontier AI models. Own deployment and operation of schedulers (SLURM, Kubernetes), specialize in a core HPC domain (GPU compute, storage, networking), build automation with Bash/Python, support researchers' workloads, and tune cluster performance and reliability.
The summary above was generated by AI
Overview

Microsoft AI is looking for experienced Member of Technical Staff, Software Engineers - Compute Infra/HPC to build the compute infra software that brings frontier AI compute online and keeps it healthy at global scale. You will work across cluster bring-up and automation, fleet and node lifecycle and health, and automated operations at global scale. The systems you build will transform newly delivered compute capacity into secure, observable, schedulable clusters and continuously recover usable capacity when hardware or software fails.

This is a hands-on software engineering role at the boundary of distributed systems and AI supercomputing. You will design control planes, APIs, workflow engines, state models, and hardware-aware automation for some of the largest GPU systems in the world. Rather than relying on manual intervention, you will turn recurring operational workflows and failure modes into durable platform capabilities that improve time to production, fleet availability, and researcher velocity.

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.

We are fortunate to partner with product teams that give our models the opportunity to reach billions of users and create immense positive impact. If you are highly ambitious, collaborative, and low ego, you will fit right in - come join us as we build the next generation of models and the computing platform behind them.

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 and build distributed services, control planes, and platform APIs for the end-to-end lifecycle of AI compute clusters, from capacity ingestion and provisioning through certification, upgrades, maintenance, repair, and decommissioning.
  • Build foundational primitives that make new capacity enablement repeatable and secure by default, including cluster bootstrap, Kubernetes control planes, networking, identity and access, image distribution, secrets, infrastructure as code, and cluster metadata across Azure and partner clouds.
  • Own software systems that reduce cluster bring-up time by automating rack and node qualification, topology validation, scale testing, and the transition from newly delivered hardware to healthy, schedulable fleet.
  • Develop the node and fleet health platform that combines telemetry, health signals, diagnostics, and lifecycle state to detect, isolate, and remediate unhealthy hardware, hosts, networks, and storage with minimal human intervention.
  • Build policy-driven and agent-assisted automation for certification, maintenance, safe rollout or rollback of software and platform components.
  • Use production evidence, benchmarks, workload profiles, and fault injection to improve system architecture, efficiency, failure detection, recovery time, and the quality of health and readiness decisions.
  • Translate incidents and repeated operational work into durable software, stronger abstractions, automated guardrails, and clear ownership boundaries rather than one-off manual procedures.
  • Partner closely with researchers, hardware health, networking, storage, security, and datacenter teams to shape the long-term architecture of Microsoft AI compute infrastructure.
  • Provide technical leadership through design reviews, architecture decisions, code quality, mentoring, and execution of complex cross-team initiatives.
  • Embody our Culture and Values.

Qualifications
Required Qualifications:
  • Bachelor's Degree in Computer Science, Computer Engineering, Electrical Engineering, or a related technical field AND 4+ years of software engineering experience building production distributed systems, infrastructure platforms, or control-plane services
    • OR equivalent experience.
  • 4+ years of experience designing and implementing scalable software for cloud, datacenter, cluster, or fleet infrastructure using one or more general-purpose languages such as Go, Rust, C++, C#, Java, or Python.
  • Experience with Kubernetes or comparable cluster-orchestration systems, Linux systems, public-cloud infrastructure, and infrastructure-as-code or declarative configuration.
  • Demonstrated ability to debug complex behavior across service, control-plane, operating-system, networking, and hardware boundaries and turn findings into robust software improvements.
  • Experience leading projects across multiple teams and communicating technical tradeoffs clearly to engineering and non-engineering stakeholders.
Preferred Qualifications:
  • Master's Degree in Computer Science or a related technical field AND 6+ years of software engineering experience building distributed systems or infrastructure platforms
    • OR equivalent experience.
  • Experience building or managing compute infrastructure at hyperscale, such as fleets with thousands of nodes, multiple clusters, heterogeneous accelerator generations, or capacity spanning multiple cloud and datacenter providers.
  • Experience with cluster and node lifecycle systems, including bare-metal provisioning, cluster bring-up, health checking, certification, maintenance, repair automation, capacity management, or decommissioning.
  • Depth in Kubernetes internals or related orchestration technologies, including controllers and operators, scheduler, autoscaler, kubelet, Cluster API, container runtimes, or workflow engines.
  • Experience building cloud foundations, including virtual networking, CNI, private connectivity, DNS, workload identity, RBAC, secrets, image and artifact distribution, and Terraform or equivalent infrastructure-as-code systems.
  • Experience designing health, diagnostics, and remediation platforms using event-driven architectures, durable workflows, state machines, telemetry pipelines, automated decisioning, and safe recovery mechanisms.
  • Low-level systems experience with Linux kernels, device drivers, firmware, BMC or Redfish, secure boot or attestation, virtualization, or hardware-health agents.
  • Experience with GPU or accelerator systems and high-performance interconnects such as InfiniBand, RoCE or RDMA, NVLink, NCCL or collective communication, as well as high-performance storage and data movement.
  • Experience owning production reliability and incident response while systematically eliminating recurring toil through software and automation.
  • Dedication to writing clean, testable, maintainable, secure, and well-documented code, with strong engineering judgment around correctness, scalability, operability, and long-term platform evolution.
  • Ability to create alignment across senior stakeholders, mentor engineers, and drive complex multi-quarter technical initiatives from architecture through production adoption.
  • Passion for learning rapidly evolving infrastructure technologies and for making enormous compute systems more reliable, efficient, understandable, and easy to use.

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.

Similar Jobs at Microloft

5 Hours Ago
Remote
United States
120K-304K Annually
Mid level
120K-304K Annually
Mid level
Automation
Develop and evaluate multimodal foundation model architectures, design datasets and pipelines, run large-scale experiments, improve training/deployment efficiency, collaborate with infrastructure and product teams, and ensure responsible, safety-aligned AI development.
Top Skills: AzureCC#C++JavaJavaScriptNumpyPandasPythonPyTorchTensorFlow
5 Hours Ago
Remote
United States
120K-261K Annually
Senior level
120K-261K Annually
Senior level
Automation
Design, implement, and debug low-level software for Azure HPC/AI VMs, focusing on hardware/software interactions, device virtualization, and GPU workload performance. Drive architecture, collaborate with partners, own reliability as an on-call DRI, and develop operational playbooks to improve stability and performance.
Top Skills: AzureCC#C++Distributed SystemsGpuHigh Performance ComputingJavaJavaScriptMachine Learning MiddlewareOperating SystemsPythonVirtual MachinesVirtualization Technologies
5 Hours Ago
Remote
United States
120K-304K Annually
Mid level
120K-304K Annually
Mid level
Automation
Design and implement algorithms, model architectures, data mixtures, and scaling laws for large-scale pre-training. Run and oversee flagship training experiments on distributed infrastructure, collaborate with infrastructure/data/post-training teams, and iterate using rigorous, data-driven ablations to advance foundation models.
Top Skills: CC#C++JavaJavaScriptLarge-Scale Distributed SystemsPython

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account