Head of RL for Humanoid Autonomy

Datamentors; Lisboa; Presencial; EUR 90 000 - 130 000; Tempo integral

Resumo da oferta

Datamentors seeks an Reinforcement Learning Lead to own the post-training stage of the Ardia humanoid platform, lifting success, precision and robustness through RL fine-tuning, reward modelling and a tight sim-to-real loop. You will set the technical direction, build training/evaluation infra, and grow a small team around it.

You will lead the RL roadmap, mentor engineers, and collaborate with perception and control teams to turn demonstrations into a dependable product.

Qualificações

• Strong, demonstrable RL expertise: PPO/GRPO and related policy-gradient methods, offline RL, RLHF/preference-based RL, and reward modelling.
• Robot learning / embodied AI experience - ideally hands-on with VLA models.
• Practical sim-to-real experience and fluency with major simulators (Isaac Lab / Isaac Gym, MuJoCo).
• Solid ML engineering: PyTorch, distributed training, GPU-efficient pipelines, reproducible experiments.

Responsabilidades

• Post-VLA RL fine-tuning - design and run the pipeline that takes a pretrained/imitation-learned VLA policy and improves it with reinforcement learning (online and offline RL, RLHF/RL-from-feedback, preference and reward-model approaches) to lift task success rates and reduce failure modes.
• Reward design & evaluation - define reward signals, success criteria, and automated evaluation harnesses that actually correlate with real-world manipulation and whole-body performance, and that catch regressions before deployment.
• Sim-to-real - build and tune the simulation-to-hardware transfer loop (domain randomization, residual policies, real-world fine-tuning) so gains in simulation hold up on the physical robot.
• Data flywheel - establish the loop that turns robot rollouts and teleop data into better policies: autonomous data collection, filtering, labelling, and continual retraining.
• Integration across the stack - work with the teams owning the orchestration layer, the VLA policy, and whole-body control so RL improvements compose cleanly rather than fighting the rest of the system.
• Technical leadership - set the RL roadmap, make build-vs-adopt calls on frameworks and tooling, mentor engineers, and represent the work to the wider team and external partners.

Conhecimentos

RL expertise

Embodied AI

Sim-to-real

PPO/GRPO

Reward modelling

Ferramentas

PyTorch

Isaac Gym

MuJoCo

GPUs & distributed

Descrição da oferta de emprego

Datamentors seeks an Reinforcement Learning Lead to own the post-training stage of the Ardia humanoid platform, lifting success, precision and robustness through RL fine-tuning, reward modelling and a tight sim-to-real loop. You will set the technical direction, build training/evaluation infra, and grow a small team around it.

You will lead the RL roadmap, mentor engineers, and collaborate with perception and control teams to turn demonstrations into a dependable product.