> Markdown version of [/jobs/ext/3969135-senior-ai-infrastructure-engineer-model-training](https://www.wearedevelopers.com/jobs/ext/3969135-senior-ai-infrastructure-engineer-model-training). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior AI Infrastructure Engineer - Model Training - **Company:** Kodiak, LLC - **Location:** Mountain View, CA, United States - **Experience:** Expert - **Salary:** $190,000.0 - $260,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, C++ (Programming Language), Profiling, Nvidia CUDA, Data Files, Shard (Database Architecture), Distributed Computing Environment, InfiniBand, Python (Programming Language), Data Streaming, AI Infrastructure, Pytorch, DeepSpeed, Information Technology, Machine Learning Operations, Mixed Precision, Megatron, Lidar, Data Pipelines - **Published:** October 27, 2026 - **Apply:** https://www.careerbuilder.com/job-details/senior-ai-infrastructure-engineer-model-training-mountain-view-ca--8d54ee52-6ba6-4c6b-8428-fa582735b72f ## About the Role Artificial Intelligence (AI), Autonomous Driving Systems, Trucking, Artificial Intelligence (AI), Amazon Web Services (AWS), Cargo/Freight, Automotive Automation, Data Sets, Light Detection and Ranging (LiDAR)\Laser Detection and Ranging (LADAR), Data Partitioning, * 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