EngineeringOn-site

Robot learning engineer

Dexmate · On-site

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Last seen by MeritLog September 12, 2026Source: AshbySource version: ashby-public-job-posting-v1

MeritLog read this listing from Dexmate's Ashby job board and last checked it on September 12, 2026.

Source: the employer's Ashby job board. Open the original listing for current details.

Job details

Work model: On-site
Salary: $100K - $300K
Location: Fremont Office
Company website: customer.io

Hiring context

How this role compares at Dexmate

Dexmate has 39 live roles in MeritLog’s catalog across 9 job families, and 25 of them are in engineering. 31 of those listings publish a pay range, a disclosure rate of 79%.

This role's posted range of $100K - $300K sits above 35% of the 26 other Dexmate roles quoted over the same currency and period.

Dexmate concentrates this hiring in:

Counted across the job boards MeritLog tracks, at the time this page was served. Pay comparisons use only listings that publish a complete range in the same currency and period.

What the role asks for

What you'd do

Design and implement state-of-the-art learning algorithms for robot manipulation, navigation, and control-from simulation to deployment on physical systems
Develop novel approaches to enhance robot dexterity and mobility using reinforcement learning, imitation learning, and foundation models, etc.
Scale ML systems for large-scale model training and fine-tuning.
Build diverse, robust manipulation skills that push the boundaries of what robots can do
Collaborate closely with hardware, controls, and systems engineers to create integrated solutions

What they're asking for

PhD in Robotics, Computer Science, Electrical Engineering, Mechanical Engineering, or related field; OR Master's degree with 1+ years industry experience; OR Bachelor's degree with 3+ years industry experienceEducation
2+ years of hands-on experience developing AI systems for robotics applicationsExperience
Deep expertise in modern robot learning techniques (reinforcement learning, imitation learning, behavior cloning, etc.)Skill
Strong proficiency in Python and deep learning frameworks (PyTorch, TensorFlow, or JAX)Skill
Proven experience conducting real robot experiments and debugging complex robotic systemsSkill
Experience with robot simulators (Isaac Gym, Isaac Sim, MuJoCo, SAPIEN, Drake, or similar)Skill
Excellent problem-solving abilities and strong communication skillsSkill
Genuine passion for robotics and building products that work in the real worldSkill
Publications at top robotics/ML conferences (RSS, CoRL, ICRA, IROS, NeurIPS, ICLR, etc.)SkillPreferred
Experience with vision-language models or foundation models for roboticsSkillPreferred
Familiarity with sim-to-real transfer techniques and domain randomizationSkillPreferred
Experience with distributed training and MLOps infrastructureSkillPreferred
Background in manipulation, grasping, or mobile manipulationSkillPreferred
Track record of taking research from prototype to productionSkillPreferred

Parsed by MeritLog from the employer’s own posting. The full description follows below.

Job description

Company Description Dexmate is building the foundation for physical AI - a unified platform that combines high-quality robotic hardware with a universal Physical AI OS, making robots as easy to build and deploy as software. Today, robotics is fragmented, slow, and closed: most builders are forced to reinvent the same stack again and again, and most ideas never make it past the prototype stage. We exist to change that. Our mission is to democratize robotics by lowering the barrier to entry, delivering a plug-and-play platform for developers, researchers, and enterprises, and cultivating an open ecosystem that accelerates the evolution of physical AI. If you want to help shape the next layer of human capability - and believe the future of robotics should be built together, not in isolation - we'd love to build it with you. Responsibilities - Design and implement state-of-the-art learning algorithms for robot manipulation, navigation, and control-from simulation to deployment on physical systems - Develop novel approaches to enhance robot dexterity and mobility using reinforcement learning, imitation learning, and foundation models, etc. - Scale ML systems for large-scale model training and fine-tuning. - Build diverse, robust manipulation skills that push the boundaries of what robots can do - Collaborate closely with hardware, controls, and systems engineers to create integrated solutions Qualifications - PhD in Robotics, Computer Science, Electrical Engineering, Mechanical Engineering, or related field; OR Master's degree with 1+ years industry experience; OR Bachelor's degree with 3+ years industry experience - 2+ years of hands-on experience developing AI systems for robotics applications - Deep expertise in modern robot learning techniques (reinforcement learning, imitation learning, behavior cloning, etc.) - Strong proficiency in Python and deep learning frameworks (PyTorch, TensorFlow, or JAX) - Proven experience conducting real robot experiments and debugging complex robotic systems - Experience with robot simulators (Isaac Gym, Isaac Sim, MuJoCo, SAPIEN, Drake, or similar) - Excellent problem-solving abilities and strong communication skills - Genuine passion for robotics and building products that work in the real world Preferred Qualifications - Publications at top robotics/ML conferences (RSS, CoRL, ICRA, IROS, NeurIPS, ICLR, etc.) - Experience with vision-language models or foundation models for robotics - Familiarity with sim-to-real transfer techniques and domain randomization - Experience with distributed training and MLOps infrastructure - Background in manipulation, grasping, or mobile manipulation - Track record of taking research from prototype to production

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