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 RobCo’s 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 RobCo’s 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 (Master’s; 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.