Member of Technical Staff – Research

About the role

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