Senior DevOps Engineer, Deep Learning Frameworks

8 Months ago • 5 Years +
Devops

Job Description

NVIDIA's Deep Learning Optimized Frameworks Group seeks a Senior DevOps Engineer to enhance their high-performing deep learning software stacks. Responsibilities include automating build, test, integration, and release processes for frameworks like TensorFlow and PyTorch; configuring and maintaining industry-standard DevOps tools (Gitlab, Jenkins, Docker, etc.); developing shared utilities; leading best practices; and identifying infrastructure needs. The ideal candidate will possess strong experience in CI/CD, SCM, and build systems, along with programming skills in Python (or similar).
Good To Have:
  • CUDA & Deep Learning Software Stack experience
  • Container & cluster tech (Kubernetes, Jenkins, etc.)
  • GPU computing systems knowledge
  • Experience with new tech incorporation
Must Have:
  • 5+ years relevant experience
  • CI/CD system automation
  • SCM & build systems expertise (Git, CMake, etc.)
  • Python (or Perl/Shell scripting)
  • Problem-solving & collaboration
Perks:
  • Highly competitive salaries
  • Extensive benefits package
  • Diverse and inclusive work environment

Add these skills to join the top 1% applicants for this job

github
game-texts
cuda
gitlab
zabbix
lxc
pytorch
deep-learning
docker
kubernetes
git
python
shell
perl
bash
tensorflow
c-make
css
jenkins

NVIDIA's Deep Learning Optimized Frameworks Group is looking for an excellent DevOps Engineer to enable the next wave of NVIDIA’s highest performing deep learning software stacks. Your role spans multiple products such as TensorFlow and PyTorch and is instrumental for streamlining development, build, and releases with modern DevOps tools. Join our technically hardworking team of software engineers and infrastructure authorities to design the systems that enable NVIDIA to stay ahead of the competition as we deliver the world's fastest deep learning frameworks.

What you'll be doing:

  • Automating and optimizing build, test, integrate, and release processes for optimized NVIDIA Deep Learning Frameworks

  • Configuring, maintaining, and building upon deployments of industry-standard tools (e.g. Gitlab, Jenkins, Docker, LXC, HyperV, CMake, Bazel)

  • Developing shared utilities for setting up systems, running tests, and recording results

  • Lead best-practices for building, testing, and releasing software

  • Identifying infrastructure needs and translating them into action

What we need to see:

  • BS or higher degree in computer science (or equivalent experience)

  • 5+ years of relevant experience

  • Strong experience setting up, maintaining, and automating continuous integration systems

  • Fluency in SCM (e.g. Github, Gitlab, Git) and build systems (e.g. Make, CMake, Bazel, Docker)

  • Adept programming skills in Python (or Perl, Shell scripting, like bash, tcsh, sh)

  • Pragmatic approach to solving problems and collaboration

  • Real passion for “it just works” automation and enabling team members

Ways to stand out from the crowd:

  • Experience with CUDA and Deep Learning Software Stack

  • Good knowledge of container and cluster technologies like slurm, kubernetes, jenkins, gitlab-ci, and zabbix

  • Experience with GPU computing systems

  • Track record of identifying useful new technologies and incorporating them into SW development flows

  • Experience as an active contributor to a SW project involving many developers

NVIDIA is at the forefront of breakthroughs in Artificial Intelligence, High-Performance Computing, and Visualization. Our teams are composed of driven, innovative professionals dedicated to pushing the boundaries of technology. We offer highly competitive salaries, an extensive benefits package, and a work environment that promotes diversity, inclusion, and flexibility. As an equal opportunity employer, we are committed to fostering a supportive and empowering workplace for all.

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