Robotics ML Infra Engineer — Edge to Cloud

general robotics corporation; Redmond (WA); On-site; USD 155,000 - 205,000; Full time

Benefits offered by this job

Medical benefits

401K

Job summary

General Robotics, based in Redmond, WA, seeks a Systems Engineer to design and optimize infrastructure powering robotics foundation models from edge devices to cloud clusters. You will shape low-latency pipelines for ML training and inference and lead distributed systems across heterogeneous compute environments.

Ideal candidates have a systems engineering or AI/ML background, strong C++, Rust, Go, or Python skills, and experience with Kubernetes, Docker, and CUDA optimization for robotics

Qualifications

• Bachelor’s degree in a technical field or equivalent experience.
• 1+ year in systems engineering, software or AI/ML systems.
• Strong skills in C++, Rust, Go or Python.
• Experience with ML frameworks and cloud infra (Kubernetes, Docker).

Responsibilities

• Design, build, and optimize systems infrastructure from edge to cloud.
• Develop low-latency pipelines for ML model training and inference.
• Architect distributed systems for multi-environment resources.
• Optimize GPU/CUDA workloads for robotics apps.
• Build containerized deployment pipelines with Kubernetes and Docker.
• Collaborate with researchers to translate model needs to scalable systems.
• Design monitoring and benchmarking tools to locate bottlenecks.
• Contribute to infrastructure tooling and open-source efforts.

Skills

C++

Rust

Go

Python

Distributed systems

ML frameworks

Education

Bachelor's degree in CS/CE/Robotics

Tools

Kubernetes

Docker

CUDA

TensorFlow

PyTorch

JAX

Slurm

Ray

Job description

General Robotics, based in Redmond, WA, seeks a Systems Engineer to design and optimize infrastructure powering robotics foundation models from edge devices to cloud clusters. You will shape low-latency pipelines for ML training and inference and lead distributed systems across heterogeneous compute environments.

Ideal candidates have a systems engineering or AI/ML background, strong C++, Rust, Go, or Python skills, and experience with Kubernetes, Docker, and CUDA optimization for robotics