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Systems Engineer - Machine Learning
General Robotics
Redmond, USA
Full-time
Mid · 1+ years experience
Onsite
USD 155000-200000 yearly / year
Discovered 2 days ago
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Role Overview
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.
Key Skills for This Role
PythonPyTorchJAXDockerKubernetesRay
Full Job Posting
Position Overview
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.
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 that makes onboarding new models faster and more reliable.
- 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.
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