Python and PyTorch: you can read a large model file, change the loss, and prove it did what you intended; a solid grasp of the ML pipeline end to end, including real sensor data and its problems. First-author work in motion forecasting or planning, generative models for sequential decision making (diffusion, flow matching), reinforcement or imitation learning for control, or closed-loop simulation and evaluation.