Machine Learning Engineer (Simulation Framework)

Join Zoox, a company focused on revolutionizing transportation through autonomous vehicles. As a Machine Learning Engineer on the Simulation Core Team, you will work at the intersection of machine learning and synthetic environments, driving ML efficiency and solving complex fidelity gaps. You will develop and optimize our GPU-based simulation framework, apply reinforcement learning concepts, and build systems for data generation. The position offers a range of benefits, including paid parental leave, health insurance, and opportunities for remote work.

• Conduire l'efficacité de l'apprentissage automatique tout en résolvant des problèmes complexes de fidélité "sim-to-sim" et "sim-to-real".
• Développer et optimiser le cadre de simulation basé sur le GPU pour soutenir des pipelines d'entraînement et de validation de machine learning complexes.
• Appliquer des concepts d'apprentissage par renforcement pour résoudre des défis complexes de comportement et de planification de trajectoire dans des environnements de simulation.
• Strong proficiency in C++ and Python for building and deploying production machine learning systems
• Deep understanding of reinforcement learning and its application in simulated or robotic environments
• Hands-on experience developing, training, and fine-tuning deep learning models using modern frameworks (e.g., JAX or PyTorch)
• PhD or Master’s in computer science, robotics, machine learning, or a related field
• Experience analyzing and bridging fidelity gaps between synthetic training data and real-world execution
• Automotive or autonomous robotics industry experience
• Experience with GPU programming (CUDA) or high-performance compute clusters
• Strong background in deterministic systems and latency optimization