Embodied AI Robotics Research Scientist

Google DeepMind; Greater London; On-site; GBP 120,000 - 180,000; Full time

Job summary

Google DeepMind is seeking a Research Scientist to advance embodied AI through large-scale experiments and deployment of innovative models. You will bridge theory and real-world applications, focusing on robot intelligence, sim-to-real transfer, and multimodal architectures to scale products and infrastructure.

Candidates will contribute to cutting-edge research, publish findings, and collaborate with partner universities and institutes worldwide, while aligning with safety and ethics priorities

Qualifications

• 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.

Responsibilities

• 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.

Skills

PhD degree

Industrial R&D experience

RL/IL/VLA experience

Foundation model optimization for on‑d

Education

PhD in quantitative field

5 years industrial R&D experience

Tools

Distillation

Pruning

Quantization

Job description

Google DeepMind is seeking a Research Scientist to advance embodied AI through large-scale experiments and deployment of innovative models. You will bridge theory and real-world applications, focusing on robot intelligence, sim-to-real transfer, and multimodal architectures to scale products and infrastructure.

Candidates will contribute to cutting-edge research, publish findings, and collaborate with partner universities and institutes worldwide, while aligning with safety and ethics priorities