Systems Engineer - Machine Learning

General Robotics

• $155K — $200K *
Enterprise Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's degree in Computer Science, Computer Engineering, or relevant field, or equivalent practical experience.
  • 1+ years of experience in ML infrastructure, model serving, or backend systems engineering.
  • Proficient in Python and skilled in transforming research code into production services.
  • Experience with ML frameworks like PyTorch or JAX, and containerized deployments (Docker, Kubernetes).
  • Knowledge of distributed serving frameworks such as Ray or Triton.
  • Familiarity with async Python and real-time communication protocols; robotics experience is a plus.
  • Experience with cloud platforms (AWS, GCP, Azure) and infrastructure-as-code tools.

Responsibilities

  • Integrate and productionize ML models into the serving infrastructure, working with research teams to convert prototypes to deployment.
  • Develop and maintain efficient low-latency pipelines for ML model inference in robotics workloads.
  • Optimize GPU workloads for real-time performance with emphasis on data transfer, memory, and concurrent requests.

Benefits

  • Medical benefits including comprehensive health insurance.
  • 401K retirement plan options.
  • Work from an innovation-focused environment in AI and robotics.
Full Job Description
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.

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