Asks for

The ad says“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.”
The ad says“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.”
The ad says“Familiarity with ML frameworks (PyTorch, JAX), containerized deployments (Docker, Kubernetes), and distributed serving frameworks (Ray, Triton, or similar).”
The ad says“Familiarity with ML frameworks (PyTorch, JAX), containerized deployments (Docker, Kubernetes), and distributed serving frameworks (Ray, Triton, or similar).”
The ad says“Familiarity with ML frameworks (PyTorch, JAX), containerized deployments (Docker, Kubernetes), and distributed serving frameworks (Ray, Triton, or similar).”
The ad says“Strong Python. Comfortable navigating unfamiliar research codebases and turning them into clean, production services.”
The ad says“Familiarity with ML frameworks (PyTorch, JAX), containerized deployments (Docker, Kubernetes), and distributed serving frameworks (Ray, Triton, or similar).”
The ad says“Familiarity with ML frameworks (PyTorch, JAX), containerized deployments (Docker, Kubernetes), and distributed serving frameworks (Ray, Triton, or similar).”
The ad says“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.”
The ad says“Familiarity with ML frameworks (PyTorch, JAX), containerized deployments (Docker, Kubernetes), and distributed serving frameworks (Ray, Triton, or similar).”

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 aspire to become the starting point for AI-powered autonomous systems across a diverse set of scenarios.

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.

Qualifications

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.

Base Salary Range

The anticipated base salary for this position is $155000-$200000. Your actual pay will be based on factors such as skills, experience, and location. In addition to base salary, this role is eligible for benefits including medical, 401K, and other health benefits.

Work Authorization

This role is open to candidates currently based in and authorized to work in the US.

Equal Opportunity Employer

General Robotics is an equal opportunity employer. We do not discriminate on the basis of any status protected by applicable law.

Accommodations

If you need a reasonable accommodation during the application or interview process, please contact: hr@generalrobotics.company