Machine Learning Engineer Intern (Scenario Simulation)

Join our team as a Machine Learning Engineer Intern, where you will work on bridging the gap between simulation and real-world applications in autonomous driving. You will develop and implement a translation layer for realistic Bird's-Eye View embeddings, optimize simulation throughput, enable closed-loop training, and support reinforcement learning. Enjoy unlimited PTO, flexible working arrangements, health benefits, equity options, professional development opportunities, and daily catered lunches.

• Développer et mettre en œuvre une couche de traduction qui convertit la vérité de base (GT) du simulateur en embeddings réalistes et "bruyants".
• Rechercher et mettre en œuvre un pipeline "raccourci" qui contourne le rendu d'image/LiDAR lent pour générer des caractéristiques BEV directement à partir des données d'état.
• Intégrer les embeddings BEV traduits dans un pipeline d'entraînement pour rendre les données synthétiques directement utilisables pour les modèles de planification.
• Proficiency in Python and deep learning frameworks (PyTorch)
• Strong foundation in deep learning, computer vision, and machine learning
• Prior experience in addressing the Sim-to-Real Gap in autonomous systems such as robotics and autonomous driving
• Prior experience with BEV / E2E Autonomous Driving Architectures (understanding of BEV generation, sensor fusion, spatial transformation)
• Experience with C++
• Experience with End-to-End (E2E) driving models
• Experience with working with simulators (CARLA, IsaacSim, Gazebo)
• Experience with curating datasets and synthetic data generation (SDG),
• Experience with ML Infras (Kubeflow, MLFlow, Weights & Biases, etc)
• Basic understanding of simulation / scenario-based testing for autonomous driving systems