SeniorStaff Research Engineer – Robot Learning (mfd)

RobCo is spearheading a revolution in modular robotics making automation radically easier more flexible and more intelligent. With over 50 million in funding from world-class investors such as Sequoia Capital and Lightspeed we are building the category-leading robotics company in Europe and the US.

As a Senior Research Engineer - Robot Learning you will drive the development adaptation and real-world deployment of cutting-edge learning-based techniques for robotic manipulation. You will work at the intersection of machine learning robotics and systems engineering - scouting state-of-the-art research and translating it into robust scalable capabilities that run on real robots every day.

You will shape the core of RobCos robot learning stack: model selection policy training evaluation frameworks and sim-to-real workflows. As a senior member of the team you will mentor junior engineers and guide key technical decisions while keeping the stack pragmatic efficient and aligned with product needs.

Your Responsibilities

• Research benchmark and evaluate state-of-the-art robot learning methods (e.g. VLA models transformers diffusion policies RL visuomotor models)

• Adapt academic models for real-world deployment with a focus on robustness latency and safety

• Develop proprietary robot learning models tailored to RobCos data hardware and modular platform

• Build scalable training data and evaluation workflows together with infrastructure and software teams

• Integrate learned policies into robotic systems including perception control and runtime pipelines

• Define clear performance metrics and build automated evaluation loops (simulation and hardware)

• Own benchmarking pipelines and ensure models meet deployment readiness standards

• Mentor junior engineers/researchers and lead technical reviews of learning-based components

• Collaborate closely with perception manipulation simulation and software teams on system-level design

• Stay current with the state of the field and guide strategic robot learning directions at RobCo

• Advanced degree (Masters; PhD preferred) in Machine Learning Robotics Computer Science or a related field

• 5-10 years of experience in robot learning research or ML for robotics (industry or academic)

• Strong grounding in imitation learning reinforcement learning and simulation-to-real transfer.Publication record at conferences like CoRL Humanoids RSS IROS NeurIPS ICLR a strong plus

• Hands-on experience deploying learned policies on real robotic systems

• Excellent Python skills; experience with PyTorch JAX HuggingFace or similar frameworks

• Ability to design experiments evaluate models rigorously and communicate results clearly

• Proven track record mentoring engineers or researchers and driving research-quality code

• Bonus: experience with VLA/foundation models robotic datasets ROS 2 or scalable training systems (Ray AWS Slurm)
  

• Shape the future of learning-based robotics from the ground up

• Research-focused environment with a direct path to real-world deployment

• Access to simulation tools large datasets real robot fleets and scalable cloud compute

• High degree of ownership autonomy and influence on long-term robot learning strategy

• Hybrid work model flexible hours and high-performance equipment
  

Join RobCo and build the next generation of ML-driven robotic intelligence.