Senior Machine Learning Engineer (Computer Vision / VLM)

Join Waymo, a leader in autonomous driving technology. As a Senior Machine Learning Engineer, you will develop and train state-of-the-art computer vision and multimodal models, design a scalable AI agent framework, and collaborate with various teams to integrate the captioning system into the broader ML development lifecycle. You will own the full system lifecycle, from advanced model development to production deployment and scaling for massive data generation. Enjoy a hybrid work model, competitive compensation, and a comprehensive benefits package.

• Développer et former des modèles de vision par ordinateur et multimodaux de pointe pour extraire des informations sémantiques riches.
• Concevoir et mettre en œuvre un cadre d'agent AI évolutif qui intègre des modèles de fondation de grande taille avec les sorties de nos modèles de perception.
• Collaborer étroitement avec les équipes d'infrastructure ML, de perception, de comportement et de fondation AI pour définir les exigences en matière de données.
• Master’s degree in Computer Science, or a related technical field
• 1+ years of demonstrated experience working with large language models (LLMs) or vision-language models (VLMs) in areas such as fine-tuning, prompting, or Retrieval-Augmented Generation (RAG)
• Experience building and managing large-scale data processing pipelines for ML training
• 4+ years of hands-on experience training and shipping deep learning models for computer vision tasks (e.g., detection, segmentation, video understanding) using Python and frameworks like PyTorch, JAX, or TensorFlow
• We prefer:
• Strong software engineering fundamentals, including designing scalable and reliable systems
• Proven ability to work autonomously and lead complex technical projects in a fast-paced R&D environment
• PhD in Computer Science, or a related technical field
• Publication record in top-tier AI conferences (e.g., NeurIPS, ICML, ICLR, CVPR)
• Hands-on experience with Reinforcement Learning, especially RLHF, RLAIF, or applying RL to language/agentic tasks
• Experience with modern techniques in self-supervised, weakly-supervised, or multi-task learning for perception
• Experience building with AI agent frameworks (e.g., LangChain, LlamaIndex) or developing autonomous agentic systems
• A track record of impactful cross-functional collaboration
• Familiarity with the challenges of multimodal perception in robotics or autonomous driving