Applied Scientist / Machine Learning Engineer
Core
Building embodied AI for autonomous driving by curating, enriching, and evaluating world-scale fleet data to improve foundation models (GAIA, LINGO) that enable vehicles to perceive, reason, and act in complex environments.
Role type
Senior Applied Scientist / Staff Machine Learning Engineer (IC)
Builds
Foundation models (generative world models, vision-language-action models) and the data flywheel powering autonomous driving systems for automakers.
Domain
Autonomous driving / Embodied AI / Robotics
Deliverable
production ML models
Required skills
Data curation, foundation model training, large-scale data wrangling, foundation-model evaluation, Python, PyTorch, active learning, embedding-based retrieval, data quality at scale
Preferred skills
Autonomous driving, robotics, VLMs, world models, reinforcement learning, reward modeling, distributed data processing, simulation-based evaluation
Technologies
PyTorch, Ray Data, Daft, Spark, Lance, Iceberg, Milvus, Turbopuffer
Responsibilities
Mine world-scale fleet data for rare, long-tail, and safety-critical events; define and build repeatable curation strategies across cities and sensor rigs; build high-quality enrichment pipelines; build and fine-tune large-scale pretrained models; push multimodal perception, reasoning, language, and action for embodied VLM/VLA; design rigorous offline and closed-loop evaluation metrics; use world-model-based evaluation to probe counterfactual scenarios.
Seniority
Senior (6+ years exp) or Staff (2+ years PhD exp), hands-on IC
