Senior Deep Learning Engineer – Autonomous Vehicles

Job 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 Apply tot his job