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Robotics Deployment Engineer Jobs in California (NOW HIRING)

Openmind

Forward Deployed Engineer

San Francisco, CA · On-site

The Role Our robots are now deployed with real customers who pay real money and expect them to work. You will be the engineer on the ground who makes that true. You will own deployments end to end ...

Noble Machines, Inc

Forward Deployed Engineer

Sunnyvale, CA · On-site

$140K - $195K/yr

Lead on-site deployment, installation, and integration of Noble Machines' robots at customer sites ... Partner with engineering, autonomy, and hardware teams to translate field learnings, edge cases ...

Figure

Helix AI Engineer, Robot Learning

San Jose, CA · On-site

Figure is an AI robotics company developing autonomous general-purpose humanoid robots. They are ... robot deployment. Responsibilities : • Design, train, evaluate, and deploy learning-based ...

Knightscope

Forward Deployed Engineer

Sunnyvale, CA · On-site

$130K - $170K/yr

Job Summary The Forward Deployed Engineer is the technical operator embedded at client sites and ... Preferred: robotics or autonomous systems deployment; physical security systems (VMS, access ...

Figure

Helix AI Engineer, Robot Learning

San Jose, CA · On-site

Figure is an AI robotics company developing autonomous general-purpose humanoid robots. They are ... robot deployment. Responsibilities : • Design, train, evaluate, and deploy learning-based ...

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Robotics Deployment Engineer information

What is a robotics deployment engineer?

Robotics Deployment Engineers are professionals who specialize in installing, integrating, and configuring robotic systems in real-world settings. They work closely with clients to ensure robots are properly set up, tested, and optimized for specific operational needs. Their responsibilities often include troubleshooting hardware and software issues, providing on-site support, and training staff on using robotic equipment. These engineers play a critical role in making sure robotics technology transitions smoothly from the lab or factory to its intended application environment.

What are some typical challenges faced by robotics deployment engineers during on-site installations?

Robotics Deployment Engineers often encounter challenges such as adapting to varying facility layouts, integrating new robotic systems with existing infrastructure, and troubleshooting unexpected hardware or software issues during deployment. Communication and collaboration with local IT, operations, and maintenance teams are key to overcoming these obstacles, as each site may present unique requirements or constraints. Being flexible and solution-oriented is essential, as timelines can be tight and successful deployment often hinges on quickly resolving integration and performance concerns.

What are the key skills and qualifications needed to thrive as a robotics deployment engineer, and why are they important?

To thrive as a Robotics Deployment Engineer, you need a strong background in robotics, mechanical or electrical engineering, and experience with system integration, often supported by a relevant engineering degree. Familiarity with programming languages (such as Python or C++), robotics middleware (like ROS), and hands-on experience with automation hardware and control systems are typically essential. Problem-solving, adaptability, and excellent communication skills help you coordinate with cross-functional teams and address client needs effectively. These skills ensure successful on-site deployment, troubleshooting, and optimization of robotic systems in diverse environments.

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Cities in California with the most Robotics Deployment Engineer job openings:

Robotics Deployment Engineer jobs near you
Infographic showing various Robotics Deployment Engineer job openings in California as of September 2026, with employment types broken down into 1% Internship, 86% Full Time, 10% Part Time, 1% Temporary, and 2% Contract. Highlights an 84% Physical, 5% Hybrid, and 11% Remote job distribution.

Robotics Engineer/Researcher - Robot Learning - Imitation Learning, Foundation Models, RL

Palo Alto, CA • On-site

Proception Inc.
See more jobs at Proception Inc.external

Other

Medical, Dental, Vision

Posted 26 days ago

Key responsibilities

  • Design and implement scalable training pipelines for general-purpose manipulation policies

  • Train large multimodal policies and push them to state-of-the-art on real tasks

  • Build the data engine behind the models, including demonstration collection, curation, filtering, and dataset design

Job description

Robot Learning Researcher/Engineer (Imitation Learning, Foundation Models, RL)

Join our team to push the frontier of robot learning. You'll train general-purpose control policies at scale - spanning imitation learning and large multimodal models - build the data and evaluation pipelines that make them work, and take policies from training runs to real robots. We care more about your ability to train models that work than about any particular robot, task, or sensor you've used before.

Requirements
  • 01 MS or PhD in Robotics, Computer Science, Machine Learning, or related field-or equivalent experience
  • 02 Strong track record training neural networks end-to-end: you can take a model from idea to a working, debugged, reproducible result
  • 03 Experience developing robot learning policies like diffusion policies, 3D policies, vision-language-action models, or video action models
  • 04 Experience training models at scale: multi-GPU/multi-node training, large datasets, long runs, and debugging throughput, stability, and scaling behavior
  • 05 Strong software engineering skills in Python and PyTorch or JAX in Linux environments (C++ a plus)
  • 06 Experience building large-scale data pipelines for robot learning - demonstration collection, curation, filtering, and dataset design
  • 07 Comfortable training policies with high-dimensional action spaces and multimodal observations (vision, proprioception, language)
  • 08 Rigorous about evaluation: designing benchmarks, running ablations, and drawing correct conclusions from noisy real-world results
  • 09 (+) Hands-on robotics experience - hardware bring-up, teleoperation and real-world data collection, on-robot deployment
  • 10 (+) Experience with high-performance simulation (MuJoCo, Isaac Gym/Lab) and sim2real techniques (domain randomization, dynamics adaptation, residual policy learning)
  • 11 (+) Familiarity with contact-rich or dexterous manipulation, tactile sensing, or differentiable simulation
Details & responsibilities
  • 01 Design and implement scalable training pipelines for general-purpose manipulation policies
  • 02 Train large multimodal policies - diffusion, 3D, vision-language-action, and video action models - and push them to state-of-the-the advantage on real tasks
  • 03 Build the data engine behind the models: demonstration collection, curation, filtering, and dataset design at scale
  • 04 Integrate visual, proprioceptive, and tactile feedback into policy architectures
  • 05 Take policies from training runs to real hardware, closing the loop with on-robot deployment and iteration
  • 06 Collaborate across AI, hardware, and perception teams to build closed-loop manipulation systems
  • 07 Publish or contribute to cutting-edge research while delivering production-quality control stacks
  • 01 Competitive salary and meaningful equity
  • 02 Full health, dental, and vision insurance
  • 03 Access to custom-built dexterous robots
  • 04 Collaboration with leading researchers in robotics and AI
  • 05 Backed by YC and top-tier investors
  • 06 High-ownership role with the opportunity to lead core initiatives in real-world robot learning
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