Senior Software Engineer - Digital Biology

at Nvidia
📍 Santa Clara, United States
USD 148,000-287,500 per year
SENIOR
✅ On-site

SCRAPED

Used Tools & Technologies

Not specified

Required Skills & Competences ?

Docker @ 4 Go @ 4 Kubernetes @ 4 Linux @ 4 Python @ 7 GitHub @ 4 GitHub Actions @ 4 CI/CD @ 4 Algorithms @ 4 MLOps @ 4 Leadership @ 4 Bash @ 4 Communication @ 4 Mathematics @ 4 Technical Leadership @ 4 PyTorch @ 7 GPU @ 4

Details

NVIDIA has been redefining computer graphics, PC gaming, and accelerated computing for more than 30 years. Today, we’re tapping the unlimited potential of AI to define the next era of computing. As part of the Digital Biology team, you’ll build and scale the AI software that powers breakthroughs in drug discovery and biological sciences. If you love moving between science, code, and the infrastructure that makes it reliable, fast, and cost-efficient, you’ll feel at home here.

Responsibilities

  • Own testing-at-scale and reliability pipelines: build hermetic, reproducible test matrices across GPU SKUs, multi-node scale, and scientific parameters relevant to the biology space.
  • Create integration and performance test harnesses for large models.
  • Productize AI algorithms: ship LLMs and geometric deep learning models into production-quality services and SDKs; ensure observability, reproducibility, and model/package versioning.
  • Develop and deploy distributed learning systems and tools to synchronize and debug workloads on thousands of GPUs.
  • Collaborate across teams: partner with applied research, AI infrastructure, and full-stack teams; contribute to and upstream improvements across the open-source ecosystem.
  • Be hands-on: dive into infra, glue code, tests, or docs to unblock the team and ship.

Requirements

  • 3+ years of relevant experience.
  • BS/MS in Computer Science, Electrical Engineering, Mathematics, Physics, or equivalent experience.
  • Strong Python and PyTorch expertise.
  • CI/CD and automation experience: GitHub Actions, YAML workflows, runners, authentication, caching, artifact stores, and release pipelines.
  • Distributed training fundamentals: DDP/FSDP, NCCL, mixed precision, data/pipe/tensor parallelism.
  • MLOps for AI: Linux, bash, containers (Docker/NGC), SLURM and/or Kubernetes.
  • Recognized for ownership and technical leadership, excellent communication, and a bias for action.

Ways to stand out

  • Experience working in mixed applied science and engineering teams, balancing production-grade requirements with research agility.
  • Systems intuition for compute efficiency: kernel optimization, IO/data pipelines, and performance tradeoffs.
  • A natural interest in biological and physical sciences and a desire to continuously learn-as-you-go.

Benefits and Compensation

  • Base salary ranges (location and level dependent):
    • Level 3: 148,000 USD - 235,750 USD
    • Level 4: 184,000 USD - 287,500 USD
  • You will also be eligible for equity and benefits. For more details, see NVIDIA benefits information.

Additional information

  • Applications for this job will be accepted at least until September 29, 2025.
  • NVIDIA is committed to fostering a diverse work environment and is an equal opportunity employer. We do not discriminate on the basis of protected characteristics.

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