Senior Machine Learning Engineer, End‑to‑End Autonomous Driving

What you'll do

• Design and implement large-scale end-to-end driving models using advanced architectures.
• Identify failure cases to drive iterative improvement of real-world performance.
• Build high-quality multimodal datasets tailored for autonomous driving systems.
• Develop and apply data-centric learning algorithms to enhance model training.
• Explore new data sources like simulation and synthetic data to improve robustness.
• Design agentic data workflows to automate discovery, labeling, evaluation, and retraining.

What we're looking for

• Strong background in modern deep learning, including transformer-based architectures and multimodal VLM/VLA models.
• Extensive experience training and deploying large-scale deep learning models on real-world datasets.
• Proficiency in Python and major deep learning frameworks like PyTorch or TensorFlow, with solid software engineering practices.
• Practical experience with data-centric methods such as active learning, curriculum learning, and outlier detection.
• Demonstrated ability to collaborate across teams and drive complex projects from prototype to production.
• Experience building and operating large-scale data pipelines for machine learning, including continuous retraining loops.