Senior Research-Ops & DevOps Engineer

Nvidia is looking for a Senior Software Engineer to join our Video/Multimedia Architecture & Algorithms (A&A) team — the people who build tomorrow’s NVENC and NVDEC, the dedicated video encode and decode engines that power streaming, cloud gaming, video conferencing and broadcast on every modern NVIDIA GPU. You will lead the infrastructure and operations for this group’s work. This includes setting up compute resources on-premises and in the cloud. You will develop distributed pipelines for large-scale regressions and experiments across hardware simulations and machine learning workloads. You will maintain the CI/CD and development environments. You will also transform one-off research workflows into reliable, repeatable, automated systems.

This is a hybrid role — 4 days per week from the office.

What You'll Be Doing
Work closely with our Architects and Algorithms Engineers to understand the needs and transform one-off research workflows into dependable, consistent, automated systems
Stand up and operate the compute the group runs on — on-prem GPU clusters, cloud bursts, queues, schedulers (Slurm / Kubernetes), container images, environments
Develop and build decentralized workflows for extensive regression testing and experiments across HW-simulations and ML workloads — and the dashboards that make sense of the results
Lead the team’s CI/CD plus the dev environments, container images and tooling everyone in the group lives in every day

What We Need To See
B.Sc. in Computer Science or Electrical/Computer Engineering
5+ years in a DevOps, SRE, MLOps, Research-Ops or platform-engineering role
Strong Linux fundamentals — shell, processes, networking, filesystems, systemd, performance tools
Strong hands-on experience in Python — confident writing production-quality code, not just scripts
Hands-on experience with at least one major Cloud ecosystem (OCI, AWS, Azure, GCP) and with Infrastructure as Code (Terraform, Pulumi or similar)
Containers and orchestration: Docker plus Kubernetes, and/or HPC schedulers like Slurm
Experience designing and bringing up CI/CD flows at scale (GitLab CI, GitHub Actions, Jenkins or similar) and operating distributed batch pipelines

Ways To Stand Out From The Crowd
Familiarity with video compression / codecs (NVENC, NVDEC, FFmpeg, GStreamer)
GPU-aware infrastructure experience: CUDA toolkit installs, driver versioning, MIG, NCCL
Reading-level comfort with C++ — enough to debug a build or trace a benchmark issue into the codec stack
Observability experience — Prometheus, Grafana, OpenTelemetry, structured logging

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

NVIDIA is committed to fostering a diverse work environment and is 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.