Senior AI Infrastructure Engineer - Model Training
Kodiak•Mountain View, CA
•Onsite
About The Position
Kodiak Robotics, Inc. is a leader in autonomous ground transportation, developing an AI-powered technology stack for commercial trucking and the public sector. The company is seeking engineers to enhance its model training infrastructure. This role focuses on improving the speed and efficiency of training AI models by optimizing data loading, distributed training, and GPU utilization. The ideal candidate will measure their impact in tokens per second and GPU utilization.
Requirements
- BS, MS, or PhD in Computer Science or a related field, and at least 2-3 years of industry experience in ML systems or infrastructure.
- Hands-on experience with distributed training frameworks and techniques (PyTorch DDP/FSDP, DeepSpeed, Megatron, NCCL) and a strong grasp of parallelism trade-offs.
- Experience building high-performance data pipelines for large-scale training, including streaming dataset formats (WebDataset, MosaicML Streaming/MDS, or similar), sharding, and storage/network-aware loading.
- Deep understanding of GPU performance: mixed precision, memory hierarchy, kernel fusion, profiling tools (Nsight, PyTorch Profiler), and interconnects (NVLink, InfiniBand).
- Strong Python skills and proficiency in PyTorch internals.
- Systems-level experience (C++/CUDA/Triton) a plus.
- Passion for building the infrastructure that lets AI for the physical world train faster, scale further, and improve continuously.
Responsibilities
- Design high-throughput data loading and streaming systems for multimodal sensor data (camera, LiDAR, radar), including dataset formats, sharding strategies, and prefetching pipelines that keep GPUs saturated.
- Build and optimize distributed training infrastructure across multi-node GPU clusters, applying data, tensor, pipeline, and fully sharded (FSDP/ZeRO) parallelism to models that don't fit on a single device.
- Maximize utilization of modern accelerators such as NVIDIA B200s through mixed-precision training (BF16/FP8), fused kernels, memory optimization, and communication/computation overlap.
- Profile end-to-end training pipelines to find and eliminate bottlenecks across storage, network, CPU preprocessing, and GPU compute.
- Develop scalable dataset construction pipelines that convert petabytes of raw driving logs into training-ready, streamable formats.
- Partner with ML teams to scale new architectures from prototype to full-cluster training runs efficiently and reliably.
Benefits
- Competitive compensation package including equity and annual bonuses
- Excellent Medical, Dental, and Vision plans through Kaiser Permanente, Cigna, and MetLife (including a medical plan with infertility benefits)
- MetLife Legal Services, Identity & Fraud Protection, Hospital Indemnity Insurance, Accident Insurance, & Critical Illness Insurance
- Flexible PTO, 10 paid holidays, and generous parental leave policies
- Dog-friendly office, free catered lunch, a fully stocked kitchen, and free EV charging
- Long Term Disability, Short Term Disability, Life Insurance
- Wellbeing Benefits - Headspace through Cigna, Calm through Kaiser, One Medical, Gympass, Spring Health through Cigna, Rula (mental health navigation)
- Fidelity 401(k)
- Commuter, FSA, Dependent Care FSA, HSA
- Various incentive programs (referral bonuses, patent bonuses, etc.)
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What This Job Offers
Job Type
Full-time
Career Level
Senior
