Senior Deep Learning Engineer – Autonomous Vehicles

Job not on LinkedIn

October 2

🏄 California – Remote

Although this job is listed in California, this company may be open to hiring remote in other states.

⛰️ Colorado – Remote

Although this job is listed in Colorado, this company may be open to hiring remote in other states.

+3 more states

🏄 California – Remote ⛰️ Colorado – Remote 🗽 New York – Remote 🤠 Texas – Remote ☕ Washington – Remote

💵 $224k - $356.5k / year

⏰ Full Time

🟠 Senior

🤖 Machine Learning Engineer

🦅 H1B Visa Sponsor

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NVIDIA

WebsiteLinkedInAll Job Openings

Artificial Intelligence • Gaming • Automotive

NVIDIA is a leading technology company specializing in accelerated computing and artificial intelligence. NVIDIA pioneers advancements in graphical processing units (GPUs), cloud computing, data centers, and virtual reality, with a focus on gaming, automotive, healthcare, and robotics industries. The company's innovations, such as NVIDIA Omniverse, transform traditional digital processes by enabling high-fidelity simulations and rendering tasks. Their applications span various industries, from autonomous vehicles using NVIDIA DRIVE to healthcare solutions with NVIDIA Clara, and AI-driven analytics and workflows.

10,000+ employees

Founded 1993

🤖 Artificial Intelligence

🎮 Gaming

📋 Description

• 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.

🎯 Requirements

• 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 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.

🏖️ Benefits

• equity • benefits