Requirements

• PhD degree in a relevant quantitative field (e.g., Robotics, Computer Science, Machine Learning), or equivalent practical experience.
• 5 years of professional research experience in an industrial research and development (R&D) laboratory.
• 3 years of experience designing, training, and scaling reinforcement learning (RL), imitation learning (IL), or multimodal generative architectures (including Vision-Language-Action (VLA) or video foundation models).
• 2 years of experience optimizing foundation models for production, utilizing techniques like distillation, model pruning, and post-training quantization to meet on-device latency and memory footprint constraints.

Nice to haves

• 3 years of experience building data pipelines, deploying production-ready systems, and experience managing multi-sensory datasets.

What you'll be doing

• Architect and train models to expand robotic capabilities and prototype concepts.
• Apply domain expertise in sim-to-real transfer, imitation learning, Vision-Language-Action (VLA) models, multi-sensory learning (tactile, audio), and model optimization (distillation, pruning, quantization).
• Propose novel ideas, address manipulation hardware requirements, and communicate results to audiences.

Perks and benefits

• Work at Google DeepMind, a pioneering AI lab focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation.
• Opportunity to contribute to real-world problems spanning machine learning, data mining, natural language processing, hardware/software performance, and more.
• Engage in collaborative research with partner universities and technical institutes worldwide.
• Be part of global teams offering diverse learning opportunities and varied career pathways.
• Strong commitment to safety, ethics, diversity, equity, and inclusion.