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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Veluto Mobility