Senior Research-Ops & DevOps Engineer

Job Title

Senior Research-Ops & DevOps Engineer

Role Summary

Work with the Video/Multimedia Architecture & Algorithms team to lead infrastructure and operations for research into NVENC/NVDEC video encode/decode engines. The role manages on-prem and cloud compute, CI/CD and development environments, and converts one-off research workflows into reliable, automated systems for large-scale regressions and experiments.

Experience Level

Senior. The posting requests 5+ years in DevOps, SRE, MLOps, Research-Ops or platform-engineering roles.

Responsibilities

Primary responsibilities include building and operating compute and platform tooling, creating reproducible research pipelines, and owning CI/CD and developer environments.

• Collaborate with architects and algorithms engineers to understand requirements and convert ad-hoc research workflows into dependable automated systems.
• Deploy and operate compute infrastructure: on-prem GPU clusters, cloud burst capacity, queues and schedulers (Slurm/Kubernetes), container images, and environments.
• Design and implement decentralized workflows for large-scale regression testing and experiments across hardware simulations and ML workloads; build dashboards to surface results.
• Lead the team's CI/CD, development environments, container images, and day-to-day tooling.

Requirements

Must-have technical skills and experience.

• 5+ years in DevOps, SRE, MLOps, Research-Ops or platform engineering (experience-level noted above).
• Strong Linux fundamentals: shell, processes, networking, filesystems, systemd, and performance tools.
• Proficient in Python with production-quality coding experience.
• Hands-on experience with at least one major cloud provider (OCI, AWS, Azure, GCP) and Infrastructure as Code (Terraform, Pulumi or similar).
• Containers and orchestration: Docker and Kubernetes, and/or HPC schedulers such as Slurm.
• Experience designing and operating CI/CD flows at scale (GitLab CI, GitHub Actions, Jenkins or similar) and running distributed batch pipelines.

Nice-to-have:

• Familiarity with video compression/codecs (NVENC, NVDEC, FFmpeg, GStreamer).
• GPU-aware infrastructure experience: CUDA installs, driver/compatibility management, MIG, NCCL.
• Reading-level comfort with C++ for debugging builds or tracing benchmark issues.
• Observability tool experience: Prometheus, Grafana, OpenTelemetry, structured logging.

Education Requirements

B.Sc. in Computer Science or Electrical/Computer Engineering specified in the posting.

About the Company

Company: NVIDIA

Headquarters: Santa Clara, California, USA

NVIDIA is a global leader in accelerated computing, renowned for its innovative solutions in AI and digital twins that transform diverse industries. The company specializes in networking technologies, providing end-to-end InfiniBand and Ethernet solutions for servers and storage that optimize performance and scalability. NVIDIA serves sectors such as high-performance computing, enterprise data centers, and cloud computing, constantly reinventing its products and services to stay ahead in the market.