Research Scientist: Post-Training

h3About Enact /h3 pThe next defining technological breakthrough will be in the physical world. We stand at a historical inflection point: bringing general-purpose intelligence into robotics. /p pAt Enact we rethink the entire robotic tech stack from model architectures and data pipelines, to the actuators and sensors that feed the model. Pushing beyond pure vision and language approaches, we build a proprioceptive nerve system, and the cortex that makes sense of it, to solve dexterity through whole-body force-awareness and deploy robots for thousands of tasks in industry and beyond. /p pWe are shaping a company where brilliant and unconventional people thrive together on solving the hardest challenges of our time. We are truth seekers. We reason from first principles, test our beliefs against reality, and trust that the best ideas can come from anyone. We move fast. We care deeply about our work and colleagues and are driven by passion to change the status quo. /p pIf this resonates, we're excited to hear from you. /p h3In This Role /h3 pYou will build the base intelligence layer for robotics, training large-scale force-aware foundation models to unlock dextrous manipulation, generalizing across tasks and environments. /p ul lipDesign and execute large-scale pre-training runs for robot foundation models, defining the architectures, objectives, and training curricula that push AI-driven manipulation beyond pixels to actions. /p /li lipOwn experiments end-to-end, from data specification through training to real-robot evaluation, to understand scaling laws, data quality effects, and architecture tradeoffs. /p /li lipBuild data mixes and evaluation sets to train and assess robots on novel, high-precision tasks, across real-world and simulated settings. /p /li lipResearch methods for improving sample efficiency and robustness, ensuring learned policies generalize reliably from training to real-world deployment. /p /li /ul h3What We're Looking For /h3 ul lipDeep experience developing large-scale predictive or generative models - including RSSM-style, JEPA, transformer, or diffusion/flow-based architectures. /p /li lipStrong probability, statistics, and ML fundamentals, paired with the ability to design rigorous experiments and separate real signal from noise or bugs in experimental data. /p /li lipPhD or equivalent research experience with a proven record of research accomplishments in machine learning, computer vision, data-science, robotics and other related fields /p /li lipStrong fundamentals in ML computing frameworks like PyTorch or JAX, with familiarity in optimizing for performance and efficiency at scale. /p /li lipMotivated to see general-purpose robotic intelligence deployed in the real world. /p /li /ul h3Bonus Points If You Have /h3 ul lipPrior experience working with real robot hardware /p /li lipLed or made significant contributions to multi-node, multi-GPU distributed training efforts. /p /li lipExperience designing or scaling data collection, annotation and mixing pipelines /p /li lipTrack record of open-source contributions or released models/datasets. /p /li lipPublications at top robotics or ML venues (CoRL, RSS, ICRA, NeurIPS, ICML, ICLR). /p /li /ul h3What we offer /h3 ul lipThe opportunity to make a real impact working on some of the biggest challenges of our time /p /li lipA fast-paced learning environment alongside an outstanding, driven team /p /li lipOwnership from day one, with the ability to iterate quickly and see your impact firsthand in an early-stage startup /p /li lipVisa sponsorship relocation benefits to hire the best in the world /p /li lipA world-class in-person setup in central Zürich, with excellent prototyping, robotics, and technical infrastructure for hands-on builders /p /li lipCompetitive compensation and meaningful equity participation /p /li /ul #J-18808-Ljbffr