Robotics Engineer - Manipulation focus

Generalrobotics
Redmond, WA
On-site

Who this role is best for

Best suited to candidates with research experience in robotics and machine learning working in high-fidelity simulation and real-world deployment environments.

Best fit for

  • Candidates with research experience in robot learning and a track record of deploying models in real-world hardware.
    — “Train, adapt, and deploy manipulation foundation models — vision-language-action (VLA) policies, world action models (WAMs), reinforcement learning, and agentic robot policies.”
  • Engineers with a background in building extensible and well-documented production-quality code for robotics systems.
    — “Develop data collection, training, and evaluation pipelines as production-quality code: extensible, well-documented, and usable by engineers outside your team.”

Things to consider

  • Must be authorized to work in the US, as the role is not open to non-US candidates.
    — “This role is open to candidates currently based in and authorized to work in the US.”
  • The role requires a balance between research and engineering, as policies must be both cutting-edge and production-ready.
    — “You'll work at the frontier of autonomous manipulation, building production-grade policies that generalize across embodiments.”

How to stand out

  • Highlight experience with sim-to-real transfer and high-fidelity simulators in your resume and interviews.
    — “Build synthetic data generation pipelines on high-fidelity simulation platforms, and drive sim-to-real transfer.”
  • Emphasize your ability to design and implement end-to-end experiments with clear reporting.
    — “Run experiments end to end — experimental design, reusable implementations, model evaluation, and clear reporting of results.”
  • Showcase publications in peer-reviewed AI and robotics venues as a demonstration of technical depth.
    — “First-author publications at peer-reviewed AI and robotics venues (NeurIPS, ICML, ICLR, CVPR, ICRA, IROS, CoRL).”
  • Demonstrate hands-on experience with modern manipulation policies like VLAs or reinforcement learning.
    — “Hands-on experience with modern manipulation policies — VLAs, world action models, reinforcement learning, imitation learning, diffusion or flow-matching policies, or agentic robot policies.”
  • Demonstrate systems-level thinking by addressing constraints like latency and compute budget in your projects.
    — “Judgment about systems constraints — latency, throughput, compute budget, memory — and the ability to factor them into model and architecture choices.”
Pace · Fast PacedCollaboration · HighAutonomy · HighDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • published research papers in AI and robotics venues
  • experience with high-fidelity simulators
  • hands-on experience with modern manipulation policies
Typical background
PhD or MS in Robotics, Computer Science, or related fieldresearch experience in robot learning, computer vision, or machine learning

Skills & requirements

Required

RoboticsMachine-learningComputer-visionDeep-learningPythonC++PyTorchJax

Preferred

Nvidia-isaac-simMujocoMani-skillAirsimCarlaLidarPoint-cloudsMeshesSegmentationDetectionTracking

Stack & domain

PythonC++PyTorchJaxNvidia Isaac SimMujocoManiskillAirsimCarlaRGB And Rgb-d CamerasLidar3D RepresentationsSegmentationDetectionTrackingLeadershipCommunicationRoboticsMachine LearningComputer Vision

About the role

Original posting from Generalrobotics via Ashby

About this Role

We're hiring Robotics Engineers to bring state-of-the-art manipulation methods into the GRID platform. You'll work at the frontier of autonomous manipulation, building production-grade policies that generalize across embodiments — from fixed-base robotic arms and mobile manipulators to humanoids. This is a role for engineers who want their research to ship. You'll move between training runs, simulation, and real hardware in customer environments.

Responsibilities

  • Design methods, tools, and infrastructure to push forward the state of the art in robotics and foundation models.
  • Define research goals informed by practical engineering concerns.
  • Train, adapt, and deploy manipulation foundation models — vision-language-action (VLA) policies, world action models (WAMs), reinforcement learning, and agentic robot policies.
  • Build synthetic data generation pipelines on high-fidelity simulation platforms, and drive sim-to-real transfer.
  • Develop data collection, training, and evaluation pipelines as production-quality code: extensible, well-documented, and usable by engineers outside your team.
  • Run experiments end to end — experimental design, reusable implementations, model evaluation, and clear reporting of results.
  • Contribute to publications and open-source releases.
  • Partner with customers to take manipulation capabilities from prototype to deployed product.

Minimum Qualifications

  • Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
  • Research experience in machine learning, robotics, and computer vision.
  • Experience with developing robotics algorithms or machine learning models at scale.
  • Programming experience in Python/C++. Good understanding of deep learning frameworks like Pytorch or Jax.
  • Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment.

Desired Qualifications

  • MS or PhD in Robotics, Computer Science, Computer Engineering, or a related technical field.
  • Direct research experience in robot learning, computer vision, or machine learning.
  • First-author publications at peer-reviewed AI and robotics venues (NeurIPS, ICML, ICLR, CVPR, ICRA, IROS, CoRL).
  • Hands-on experience with modern manipulation policies — VLAs, world action models, reinforcement learning, imitation learning, diffusion or flow-matching policies, or agentic robot policies.
  • Experience with high-fidelity simulators such as NVIDIA Isaac Sim, MuJoCo, ManiSkill, AirSim, or CARLA, including domain randomization and sim-to-real workflows.
  • Familiarity with modern perception stacks and sensing modalities: RGB and RGB-D cameras, LiDAR, 3D representations (point clouds, meshes), and segmentation, detection, and tracking.
  • Judgment about systems constraints — latency, throughput, compute budget, memory — and the ability to factor them into model and architecture choices.

About General Robotics

General Robotics is building the intelligence grid for physical AI — the platform that makes any robot, from robotic arms to humanoids, genuinely intelligent. Headquartered in Redmond, Washington, we're venture backed, including by Accenture, who invested in General Robotics in 2026 to advance Physical AI-powered robotics in manufacturing and logistics, and we're also part of Microsoft's Startups Pegasus Program. Our team's work spans some of the most widely adopted robotics and AI research to come out of Microsoft Research, Google Research and DeepMind — including AirSim, PACT, ClimaX, Tensorflow Object Detection and VideoPoet.

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

Source: Generalrobotics careers (Ashby)

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