ML Engineer, Autonomous Driving Planning and Prediction

We are seeking a ML Engineer, Autonomous Driving Planning and Prediction to join our team This role is based in Newark, CA and requires employees to be onsite five days a week.

Role:

· Design, develop, and evaluate cutting-edge machine learning architectures for autonomous driving world modeling and prediction, and ego motion planning

· Prototype, engineer, test, release, and launch ML-based features autonomous driving systems

· Conduct research into state-of-the-art ML methods such as foundational model or LLM based architectures and their use case in planning and prediction.

· Analyze data from simulation and fleet logs to identify and extract critical driving scenarios. Partake in creating data based foundational world models for simulation and synthetic data generation

· Support data curation, storage, and transport workflows to facilitate automated inference and model development

Required Qualifications:

· Master’s or Ph.D. in Computer Science, Robotics, Machine Learning, or a related field

· Expert-level proficiency in Python and ML libraries such as PyTorch or TensorFlow

· Proficiency in C++ and strong hands-on experience with software engineering design principles

· Proven experience deploying production systems that integrate large-scale ML models, evaluation pipelines, and performance metrics

· Demonstrated experience designing scalable and efficient deep learning models

· Understanding of traditional (non-ML) planning methods

· Background in at least one of the following: perception, environment modeling, prediction, or planning in autonomous vehicles, or robotic applications

Preferred Qualifications:

· 3+ years of experience in ML development, particularly in large-scale data and real-time systems

· Academic or hands-on experience with imitation learning, reinforcement learning, or simulation-based training

· Experience working with foundational models, large language models (LLMs), or end-to-end AV planning systems