Machine Learning Engineer (Closed Loop)
Core
Developing next-generation generative world models and planners for closed-loop autonomous driving simulation and evaluation.
Role type
Senior IC machine learning engineer (generative world models)
Builds
Generative simulation models (e.g., GAIA) for faster training, broader testing, and scalable deployment of autonomous driving systems.
Domain
Autonomous driving, generative AI, world modeling
Deliverable
production ML models
Required skills
Generative video modeling, diffusion models, latent-video models, high-dimensional temporal data processing, PyTorch engineering, research-grade production tooling, model optimization (latency reduction), ablation study design, reinforcement learning integration
Preferred skills
Autonomous vehicles (AVs), robotics, simulation, synthetic-to-real transfer
Technologies
PyTorch, diffusion models, transformers, latent compression
Responsibilities
Invent efficient generative world-models for real-time roll-outs and scene editing; Architect interactive world models for agent/human stepping; Optimize end-to-end performance from latent compression to context pruning; Define metrics for long-horizon coherence and physics fidelity; Integrate models into closed-loop training and evaluate sim-to-real gap; Mentor junior researchers and publish at top venues
Seniority
Senior, hands-on IC with mentorship