As a founding hire at Adexis, you will own the post-training recipe that transforms foundation models into reliable, dexterous robotic behavior. You will bridge the gap between world representations and physical execution, designing the imitation and reinforcement learning strategies that allow robots to feel and manipulate the world with human-level precision.
Member of Technical Staff – Post-Training at Adexis
Adexis is bringing the power of touch to machines, building a frontier research lab in London to solve the final frontier of Physical AI: dexterous manipulation. As a founding Member of Technical Staff for Post-Training, you will own the critical recipe that turns a foundation model into a policy that can actually feel and act. Join a world-class team from Anthropic, Google DeepMind, and ElevenLabs to build the somatosensory cortex for robots. This is a rare opportunity to define the technical vision of a project aimed at physical general intelligence, backed by leading VCs and an elite leadership team.
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Location
London, United Kingdom
Compensation
£150k-£225k + Equity
Company
Adexis
Role overview
AI3–10+ employees
Founded in July 2026, Adexis is a London-based frontier robotics lab. We are solving dexterity by building the somatosensory cortex for Physical AI. Machines can speak our language and see our world, but they are still numb. Adexis will bring them the power of touch on the path to physical general intelligence. We are backed by leading VCs and angels from Anthropic, Google DeepMind, and ElevenLabs.
What you will do
- Architect the entire post-training stack, converting pretrained foundation models into dexterous control policies using teleoperated demonstration data and imitation learning.
- Close the sim-to-real and human-to-robot gaps, ensuring policies learned from demonstrations survive contact and maintain reliability on physical hardware.
- Design and implement comprehensive evaluation frameworks to catch policy failures that are invisible offline but catastrophic in real-world contact-rich environments.
Who this is a fit for
- Proven experience training manipulation policies and deploying them on real hardware, with a deep understanding of why policies fail upon contact.
- Deep expertise in imitation learning and reinforcement learning, with the judgment to determine when RL is necessary despite its inherent training instability.
- A strong technical perspective on learning dexterous, contact-rich skills and experience with teleoperation systems or learning from human-led demonstrations.
Why this role is remarkable
- Join a high-density founding team of outlier researchers from Anthropic, Google DeepMind, and ElevenLabs to solve the hardest problem in embodied intelligence.
- Own the critical technical boundary between world models and physical action, defining how machines learn the power of touch and dexterous manipulation.
- Benefit from a talent-dense culture inspired by Bell Labs and Skunkworks, supported by top-tier VCs and a leadership team with deep experience scaling AI.
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