
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.
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.
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