Hardware Systems Engineering

Systems Engineer
General Robotics is an AI research and deployment company building a platform for general robot intelligence. Our mission is to enable rapid, robust, and safe deployment of general intelligence for autonomous systems and robotics. We are seeking a Systems Engineer to join our team in Redmond, WA. We build and optimize the infrastructure that powers generalized robotics foundation models — spanning edge devices to cloud GPU clusters — with a focus on low latency, high throughput, and efficient resource utilization across form factors such as aerial, ground, manipulation, and others.
We are looking for strong candidates who have a background in systems engineering and AI/ML infrastructure, with experience in areas like systems programming; containerized deployments; and ML training and inference optimization. By applying to this role, you will be considered for multiple teams, such as platform infrastructure, ML systems, and edge deployment.
Systems Engineer Responsibilities

Design, build, and optimize systems infrastructure spanning edge devices to cloud GPU clusters for robotics workloads.
Develop and maintain low-latency, high-throughput pipelines for ML model training and inference.
Optimize GPU/CUDA workloads and accelerate ML frameworks (PyTorch, JAX, TensorFlow) for robotics applications.
Build and maintain containerized deployment pipelines using Kubernetes and Docker.
Design monitoring, profiling, and benchmarking tools to identify and resolve performance bottlenecks.
Bachelor's degree in Computer Science, Computer Engineering, Robotics, relevant technical field, or equivalent practical experience. 1+ years of experience in systems engineering, software engineering, robotics, or AI/ML systems.

• Strong systems programming skills in one or more of: C++, Rust, Go, Python.
• Solid understanding of operating systems, networking, and distributed systems fundamentals.
• Experience with ML frameworks (PyTorch, JAX, TensorFlow) and cloud infrastructure (Kubernetes, Docker).
• Experience with GPU programming and CUDA optimization for ML workloads.
• Experience designing and scaling distributed training infrastructure for large foundation models.
• Familiarity with cloud platforms (AWS, GCP, Azure) and infrastructure-as-code tooling.
• Familiarity with real-time systems, embedded platforms, or edge deployment for robotics.
• Experience with high-performance networking, storage systems, or scheduler design (e.g., In addition to base salary, this role is eligible for benefits including medical, 401K and other health benefits.

General Robotics is an equal opportunity employer. If you need a reasonable accommodation during the application or interview process, please contact: