Senior DGX Cloud Software Engineer - Infrastructure Automation and Distributed Systems

1 Month ago • 5 Years + • DevOps • $144,000 PA - $270,250 PA

Job Summary

Job Description

As a Senior DGX Cloud Software Engineer, you will design, build, and run cloud infrastructure services for AI training and inference development. Responsibilities include integrating, migrating, updating, and decommissioning systems; defining service level objectives and error budgets; automating tasks; participating in on-call rotations; consulting with peer teams on best practices; and fostering a collaborative culture. You will work with large-scale private or public cloud systems, requiring fully automated management under active customer consumption in production. The role demands proficiency in Python or Go, expertise in infrastructure automation and distributed systems, and in-depth knowledge of Linux, Kubernetes, and distributed storage.
Must have:
  • Proficiency in Python or Go
  • 5+ years experience in infrastructure and fleet management
  • Experience with infrastructure automation and distributed systems
  • In-depth knowledge of Linux, Kubernetes, and distributed storage
  • BS in Computer Science or related field
Good to have:
  • Experience with bare metal as a service (BMaaS)
  • Multi-cloud infrastructure experience
  • Experience with accelerated compute technologies (BlueField, Infiniband)
  • Experience teaching reliability engineering
Perks:
  • Equity
  • Benefits

Job Details

We are seeking Software Engineers with previous experience building and running private and public clouds at production scale. As part of the DGX Cloud team, you’ll have the opportunity to support our customers’ journeys in AI training and inference development by building the platforms, tools, and services that defend the operational capacity of our bare-metal, accelerated compute infrastructure and codify reliability best-practices in the broader DGX Cloud platform ecosystem.

What you’ll be doing:

  • Design, build, and run cloud infrastructure services in scope to meet our business goals performing integrations, migrations, bringups, updates, and decommissions as necessary.

  • Participate in the definition of our internal facing service level objectives and error budgets as part of our overall observability strategy.

  • Eliminate toil or automate it where the ROI of building and maintaining automation is worth it.

  • Practice sustainable blameless incident prevention and incident response while being a member of an on-call rotation.

  • Consult with and provide consultation for peer teams on systems design best practices.

  • Participate in a supportive culture of values-driven introspection, communication, and self-organization

What we need to see:

  • Proficiency in one or more of the following programming languages: Python or Go

  • BS degree in Computer Science or a related technical field involving coding (e.g., physics or mathematics) or equivalent experience.

  • 5+ years of relevant experience in infrastructure and fleet management engineering.

  • Experience with infrastructure automation and distributed systems design developing tools for running large scale private or public cloud systems at scales requiring fully automated management and under active customer consumption in production.

  • A track record demonstrating a mix of initiating your own projects, convincing others to collaborate with you, and collaborating well on projects initiated by others.

  • In-depth knowledge in one or more of the following: Linux, Slurm, Kubernetes, Local and Distributed Storage, and Systems Networking.

Ways to stand out from the crowd:

  • Demonstrating a systematic problem-solving approach, coupled with clear communication skills and a willingness to take ownership and get results such as experience driving a build / reuse / buy decision.

  • Experience working with or developing bare metal as a service (BMaaS) associated systems. For example, vending BMaaS, or Slurm running on containers, or vending Kubernetes clusters. Experience working with or developing multi-cloud infrastructure services. Experience teaching reliability engineering (e.g. SRE) and/or other scale-oriented cloud systems practices to peers and/or other companies (e.g. CRE). Experience in running private or public cloud systems based on one or more of Kubernetes, OpenStack, Docker or Slurm.

  • Experience with accelerated compute and communications technologies such BlueField Networking, Infiniband topologies, NVMesh, and/or the NVIDIA Collective Communication Library (NCCL). Experience working with a centralized security organization to prioritize and mitigate security risks. Prior experience in a ML/AI focused role or on a team matching specific keywords is welcome but not required.

NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables outstanding creativity and discovery, and powers what were once science fiction inventions from artificial intelligence to autonomous cars. NVIDIA is looking for great people like you to help us accelerate the next wave of artificial intelligence.

NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most hard-working and dedicated people in the world working for us. If you're creative and autonomous, we want to hear from you!

The base salary range is 144,000 USD - 270,250 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.

You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

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About The Company

Since its founding in 1993, NVIDIA (NASDAQ: NVDA) has been a pioneer in accelerated computing. The company’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined computer graphics, ignited the era of modern AI and is fueling the creation of the metaverse. NVIDIA is now a full-stack computing company with data-center-scale offerings that are reshaping industry.

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