Systems Engineer

The role

This person will design, build, and optimize systems infrastructure spanning edge devices to cloud GPU clusters for robotics workloads. They will develop low-latency pipelines and manage distributed systems for ML model training and inference.

What you will do

• 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.
• Architect and manage distributed systems for efficient resource utilization across heterogeneous compute environments.
• Optimize GPU/CUDA workloads and accelerate ML frameworks (PyTorch, JAX, TensorFlow) for robotics applications.
• Build and maintain containerized deployment pipelines using Kubernetes and Docker.
• Collaborate with research teams to translate model requirements into scalable, production-grade systems.
• Design monitoring, profiling, and benchmarking tools to identify and resolve performance bottlenecks.
• Contribute to infrastructure tooling and open-sourcing efforts.

Required qualifications

• 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., Slurm, Ray).
• Good understanding of ML model architectures and the ability to factor systems constraints into research decisions.

Nice to have

• Master's degree preferred

Benefits

• medical
• 401K
• other health benefits

Before you apply

• Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment.
• This role is open to candidates currently based in and authorized to work in the US.

About the company

General Robotics is an AI research and deployment company building a platform for general robot intelligence. Their mission is to enable rapid, robust, and safe deployment of general intelligence for autonomous systems and robotics.