Machine Learning Engineer - Simulation Framework

📋 Description Develop GPU-based simulation framework for ML training and validation. Apply reinforcement learning to behavior and path planning in simulation. Bridge sim-to-sim and sim-to-real fidelity gaps between ML sims and real vehicle execution. Build systems for autonomy users to self-serve data generation and accelerate training iterations. Write robust, production-ready code to integrate ML algorithms into core simulation. 🎯 Requirements PhD or Master’s in CS, robotics, ML, or related field. Deep understanding of reinforcement learning in simulated/robotic environments. Hands-on experience training DL models using JAX or PyTorch. Strong proficiency in C++ and Python for production ML systems. Experience bridging fidelity gaps between synthetic data and real-world execution. Experience with GPU programming (CUDA) or HPC clusters. 🎁 Benefits RSUs and stock appreciation rights. Health, disability, and life insurance. Paid time off and flexible leave policies.