Senior AI Infrastructure Engineer

Responsibilities

• Design high-throughput data loading and streaming systems for multimodal sensor data including camera, LiDAR, and radar
• Build and optimize distributed training infrastructure across multi-node GPU clusters using parallelism techniques like FSDP and ZeRO
• Maximize utilization of modern accelerators such as NVIDIA B200s through mixed-precision training and memory optimization
• Profile end-to-end training pipelines to eliminate bottlenecks across storage, network, and compute
• Develop scalable dataset construction pipelines to convert petabytes of raw driving logs into training-ready formats
• Partner with ML teams to scale new architectures from prototype to full-cluster training runs

Requirements

• BS, MS, or PhD in Computer Science or a related field
• 2-3 years of industry experience in ML systems or infrastructure
• Hands-on experience with distributed training frameworks like PyTorch DDP/FSDP, DeepSpeed, or Megatron
• Experience building high-performance data pipelines and streaming dataset formats
• Deep understanding of GPU performance, memory hierarchy, and profiling tools like Nsight
• Strong Python skills and proficiency in PyTorch internals

Preferred Qualifications

• Systems-level experience with C++, CUDA, or Triton

About the Company

Kodiak Robotics is a leader in autonomous ground transportation, developing an AI-powered technology stack purpose-built for commercial trucking and the public sector.