ML Systems Engineer, Robotics

Scale's ML Systems Engineer on the Physical AI team designs and builds scalable platforms for serving foundation models tailored for physical agents, collaborating with robotics researchers and CV engineers to optimize models for production and research environments. Responsibilities include building fault-tolerant, high-performance backend systems for robotics-related models, developing an internal platform for model capability discovery to accelerate iteration, conducting architecture/design reviews for scalability, reliability and security, and implementing observability solutions to monitor real-time model inference. Ideal candidates have 4+ years of experience in ML infrastructure, CUDA/kernel optimizations for cloud environments, and strong systems programming skills across Python, Go, Rust, or C++, plus experience with Docker/Kubernetes and cloud providers (AWS/GCP) and Terraform. Nice-to-haves include exposure to VLA models, high-performance video processing or 3D data handling, and robotics middleware like ROS/ROS2. Compensation includes base salary, equity, and benefits, with a stated base salary range for San Francisco of $248,800—$311,000 USD, and a 90-day waiting period before reconsidering candidates.