At Veluto, we’re building the bikes for the future of urban transportation. As a seed-stage startup, every hire shapes the product, and we’re looking for the person who will own how our vehicles decide where to go and how they execute it smoothly and safely.
You’ll design and ship the planning and control stack end to end. That means fast rule-based baselines and classical controllers to get us moving, and modern learning-based approaches to take us further.
Hard requirements
- Proven experience building motion and behavior planners for autonomous systems (cars, bikes, mobile robots, or similar)
- Strong background in vehicle control: MPC, LQR, PID, and trajectory tracking
- Strong grounding in learning-based planning and control: reinforcement learning, imitation learning, and diffusion or other generative approaches
- Hands-on experience with classical and rule-based planners (sampling, optimization, state machines) for baselines and fast iteration
- Solid understanding of vehicle dynamics and system modeling
- Excellent Python and C++ skills; experience with PyTorch and ROS 2 is a plus
- Experience taking planners and controllers from simulation to real hardware
- MSc or PhD in Robotics, Control Engineering, CS, or a related field, or equivalent experience
Soft requirements
- Startup mindset: you prefer shipping over perfecting and are comfortable with ambiguity
- Ownership: you’ll define the roadmap, not just follow it
- Pragmatism: you know when a simple rule or PID beats a neural network
- Vision: you know when a neural network beats any rule or PID, and you push the state of the art into real-world deployment
- Clear communicator who works closely with hardware, perception, and mechanical teams
- Curiosity and drive to keep up with fast-moving research
What we offer
Real ownership and impact from day one
- #Hiring #AutonomousSystems #MotionPlanning #ControlEngineering #ReinforcementLearning #ImitationLearning #Startup #Mobility
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