Senior Software Engineer - Digital Biology

Nvidia • Santa Clara, CA

98d • $148,000 - $235,750

About The Position

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.

Requirements

• 3+ years of relevant experience.
• BS/MS in CS, EE, Math, Physics, or equivalent experience.
• Python, 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, with excellent communication and a bias for action.

Nice To Haves

• Worked in mixed applied science and engineering teams, familiar with the production-grade vs agility balance required to make forward progress.
• Systems intuition for compute efficiency: kernel optimization, IO/data pipelines, and performance tradeoffs.
• A natural interest in biological and physical sciences and desire to continuously learn-as-you-go.

Responsibilities

• Own testing-at-scale and reliability pipelines: Build hermetic, reproducible test matrices across GPUs 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 whatever is needed—infra, glue code, tests, or docs—to unblock the team and ship.

Benefits

• Competitive salaries
• Generous benefits package
• Equity eligibility

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Industry: Computer and Electronic Product Manufacturing
• Education Level: Bachelor's degree