Building robust training pipelines and libraries to handle massive video datasets and enable rapid experimentation.
Collaborating with researchers, model engineers, and internal platform teams to enhance efficiency, minimize stalls, and improve training availability.
Owning core infrastructure components such as orchestration libraries, distributed training frameworks, and fault-resilient training systems.
Partnering with leadership to ensure infrastructure scales with growing GPU capacity and dataset size while maintaining developer efficiency and stability.
What we need to see
BS, MS, or PhD in Computer Science, Electrical/Computer Engineering, or a related field, or equivalent experience.
12+ years of professional experience building and scaling high-performance distributed systems, ideally in ML, HPC, or large-scale data infrastructure.
Extensive knowledge in deep learning frameworks (PyTorch is preferred), large scale training (DDP/FSDP, NCCL, tensor/pipeline parallelism), and performance profiling.
Strong systems background: datacenter networking (RoCE, IB), parallel filesystems (Lustre), storage systems, schedulers (Slurm, Kubernetes, etc.).
Proficiency in Python with experience writing production-grade libraries, orchestration layers, and automation tools.
Ability to work closely with multi-functional teams (ML researchers, infra engineers, product leads) and translate requirements into robust systems.
Ways to stand out from the crowd
Shown experience scaling large GPU training clusters with >1,000 GPUs.
Expertise in fault resilience and high availability, including elastic training and large-scale observability.
Tried leadership skills as a hands-on technical authority, encouraging others and establishing guidelines for ML systems engineering.
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You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until November 10, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and 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.
