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General Robotics

Robot type
Robot AI and Software
Location
RedmondWashingtonUSA
Job type
Artificial Intelligence
Posted
Mar 29, 2026
Full-time

Systems Engineer - Machine Learning

Job description

We are seeking an ML Engineer to join our team in Redmond, WA. We build and optimize the platform that serves ML models to robots in real-time — from perception and planning to foundation models — with a focus on low latency, high throughput, reliable and robust robot-to-cloud communication.

We are looking for strong candidates who have a background in ML infrastructure and model serving, with experience in areas like CUDA kernel programming; distributed serving frameworks; real-time streaming; and taking research models to production. By applying to this role, you will be considered for multiple teams, such as platform infrastructure, ML systems, and edge deployment.

Job responsibilities

  • Integrate and productionize state-of-the-art ML models into our serving infrastructure, collaborating with research teams to bring new architectures from prototype to deployment.Contribute to infrastructure tooling…
  • Develop and maintain low-latency, high-throughput pipelines for ML model inference across robotics workloads.
  • Optimize GPU workloads and accelerate ML frameworks for real-time performance: data transfer, memory management, batching, serialization, and concurrent request handling.

Job requirements

  • Bachelor’s degree in Computer Science, Computer Engineering, or relevant technical field, or equivalent practical experience.
  • 1+ years of experience in ML infrastructure, model serving, or backend systems engineering.
  • Strong Python. Comfortable navigating unfamiliar research codebases and turning them into clean, production services.
  • Familiarity with ML frameworks (PyTorch, JAX), containerized deployments (Docker, Kubernetes), and distributed serving frameworks (Ray, Triton, or similar).
  • Familiarity with async Python, real-time communication protocols, and robotics systems is a plus.
  • Familiarity with cloud platforms (AWS, GCP, Azure) and infrastructure-as-code tooling.
  • Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment.
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