Senior AI Infrastructure Engineer

Who we are Gatik, the leader in autonomous middle-mile logistics, is revolutionizing the B2B supply chain with its autonomous transportation-as-a-service (ATaaS) solution and prioritizing safe, consistent deliveries while streamlining freight movement by reducing congestion. The company focuses on short-haul, B2B logistics for Fortune 500 retailers and in 2021 launched the world’s first fully driverless commercial transportation service with Walmart. Gatik's Class 3-7 autonomous trucks are commercially deployed across major markets, including Texas, Arkansas, and Ontario, Canada, driving innovation in freight transportation. The company's proprietary Level 4 autonomous technology, Gatik Carrier™, is custom-built to transport freight safely and efficiently between pick-up and drop-off locations on the middle mile. With robust capabilities in both highway and urban environments, Gatik Carrier™ serves as an all-encompassing solution that integrates advanced software and hardware powering the fleet, facilitating effortless integration into customers' logistics operations. About the role We are seeking a Senior AI Infrastructure Engineer to design, build, and scale the high-performance AI platform powering our autonomous driving models. While researchers focus on developing perception, planning, and world models, you will be responsible for the underlying infrastructure that ena [... source excerpt omitted ...] the gap between research and production, ensuring our AI stack is scalable, resilient, and highly efficient This role is onsite 5 days a week at our Santa Clara, CA office! What you'll do Distributed Training & ML Systems Support Scale Research Workloads: Enable researchers to scale complex models (VLA, World Models) across multi-node setups using PyTorch Distributed, and Ray Train. Performance Optimization: Architect and optimize multi-GPU setups, ensuring efficient model parallelism and data parallelism techniques across H100/A100 clusters. Networking & Hardware Tuning: Optimize low-level communication (e.g., NCCL tuning, InfiniBand, or RoCE v2) to minimize latency for [... source excerpt omitted ...] Helm. Data & CI/CD: Proficiency in Apache Airflow, Kafka, Spark, and GitOps automation. Core Skills: Proficiency in Python and Bash; experience with Go or Rust is a plus Bonus Qualifications Advanced AI Protocols: Familiarity with the Model Context Protocol (MCP) to standardize how AI agents interact with internal databases and orchestration APIs. Hybrid & Physical AI: Experience in hybrid cloud and on-prem GPU cluster management for Physical AI workloads (e.g., 3DGS, World Models). Agentic Observability: Experience utilizing LLMs for semantic monitoring and log analysis to detect complex distributed system failures that traditional threshold-based alerts miss. Salary Ranges -