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Waymo is looking to develop machine learning solutions addressing open problems in autonomous driving, specifically focusing on spatial-temporal visual reasoning using large language and vision models to improve the safety and capabilities of their autonomous driving technology.

Requirements

• 5+ years of experience in Machine Learning, with a focus on large-scale model development (LLM, VLM, or similar foundation models).
• Proven expertise in visual reasoning, scene understanding, or related areas within autonomous driving, robotics, or computer vision.
• Strong coding proficiency in Python and deep learning frameworks (e.g., Jax, TensorFlow, PyTorch).
• Hands-on experience with model training, evaluation, and deployment in a production environment.
• Experience with advanced training techniques, such as Supervised Fine-Tuning (SFT) or Reinforcement Learning (RL) for language/vision models.
• Familiarity with large-scale data curation and quality assurance processes for multimodal datasets (e.g., rationale/QA data).
• Background in autonomous vehicle perception, motion planning, or decision-making systems.

Responsibilities

• Design and implement cutting-edge models and algorithms for spatial-temporal visual reasoning in autonomous driving scenarios, utilizing large language and vision models (LLM/VLM).
• Develop and maintain robust training and evaluation pipelines for VLM models, focusing on metrics relevant to decision-making rationale and free-form question answering.
• Collaborate with ML engineers and researchers to integrate visual reasoning capabilities into product systems.
• Lead the effort to set up proper large-scale rationale/QA data and establish rigorous evaluation metrics for visual reasoning tasks.
• Explore and implement advanced techniques, including Supervised Fine-Tuning (SFT) and Reinforcement Learning (RL), to optimize model performance for complex visual reasoning challenges.
• Analyze and interpret large-scale sensor data to identify key challenges and opportunities for improving LLM/VLM performance in real-world driving environments.

Other

• In this hybrid role, you will report to a Staff Research Scientist.
• Master's degree in Computer Science, Electrical Engineering, or a related field, or equivalent practical experience.
• Publications in top-tier machine learning or computer vision conferences (e.g., NeurIPS, ICML, CVPR, ICCV, ECCV).
• PhD in a relevant field.