Member of Technical Staff – Research

About Adexis

Adexis is a London-based frontier research lab solving dexterous manipulation. Our mission is to bring machines the power of touch on the path to physical general intelligence, bringing about a future of abundance.

We are building a lean, talent dense organisation, inspired by history's great groups — the Manhattan Project, Apollo, Bell Labs, Skunkworks — where aggregating outlier individuals drove collective output that changed history.

We are backed by leading investors, and researchers from Anthropic, ElevenLabs, Google Deepmind and more.

Member of Technical Staff — Research

As a founding research hire, you could work across pre or post-training for our visuo-tactile foundation model. This might include:

• Own the model architecture end to end: how visual and tactile signals are tokenized, fused or kept separate, and learned jointly.

• Make the hard representational calls: what a contact signal is at the token level, how it aligns in time with vision, and how the two modalities trade off when they disagree.

• Own the post-training stack: how we adapt a pretrained model into a control policy using teleoperated demonstration data.

• Design the recipe: demonstration collection strategy, imitation and any reinforcement or self-improvement stages, and the full sequence from foundation model to deployable policy.

• Close the sim-to-real and human-to-robot gaps: make a policy learned from human demonstration survive contact with the real world.

• Define what good behaviour is and build the evaluation that catches a policy that looks good offline and fails on hardware.

You might be a fit if you

• Have trained large multimodal or sequence models from scratch and owned the recipe — the data mix, curricula, ablations, debugging silent failures.

• Have strong instincts for multimodal fusion.

• Have trained manipulation policies and put them on real hardware — you know the specific pain of a policy that demos well and dies on contact.

• Know imitation learning deeply and know when reinforcement is worth the instability.

• Have a point of view on learning dexterous, contact-rich skills rather than pick-and-place.

• Bonus: teleoperation systems, learning from human demonstration, real-world RL.

We seek a high ownership individual up to the task of defining this vision. This is a founding research role and will be compensated accordingly with equity.

Compensation & benefits

• Salary: £150–225k

• Equity: 0.5-2.5%

• Private healthcare with AXA

• Top of the line equipment