Note: The job is a remote job and is open to candidates in USA. NVIDIA has been a leader in computer graphics and AI innovation for over 25 years. They are seeking a Senior Deep Learning Engineer to enhance their Autonomous Vehicles project by building and scaling training libraries and infrastructure for autonomous driving models, collaborating closely with various teams to improve efficiency and safety.

Responsibilities

Crafting, scaling, and hardening deep learning infrastructure libraries and frameworks for training on multi-thousand GPU clusters.
Improving efficiency throughout the training stack: data loaders, distributed training, scheduling, and performance monitoring.
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.

Skills

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 and C++, 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.
Shown experience scaling large GPU training clusters with >1,000 GPUs.
Contributions to open-source ML systems libraries (e.g., PyTorch, NCCL, FSDP, schedulers, storage clients).
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.
Familiarity with reinforcement learning (RL) at scale, particularly in the context of simulation-heavy workloads.

Education Requirements

BS, MS, or PhD in Computer Science, Electrical/Computer Engineering, or a related field, or equivalent experience.

Benefits

Equity
Benefits

Company Overview

NVIDIA is a computing platform company operating at the intersection of graphics, HPC, and AI. It was founded in 1993, and is headquartered in Santa Clara, California, USA, with a workforce of 10001+ employees. Its website is https://www.nvidia.com.

Company H1B Sponsorship

NVIDIA has a track record of offering H1B sponsorships, with 1019 in 2025, 1361 in 2024, 977 in 2023, 835 in 2022, 601 in 2021, 529 in 2020. Please note that this does not guarantee sponsorship for this specific role.

[Remote] Senior Deep Learning Engineer – Autonomous Vehicles

Job Type