Research Scientist, Human Data, Robotics, DeepMind

• Design, implement, train and evaluate large models and algorithms for robotic agents, making breakthroughs and unlocking new robot capabilities.
• Write software to implement research ideas and iterate quickly, working effectively with a large collaborative team with fast-paced agendas to meet ambitious research goals.
• Develop methodologies and design and conduct experiments for incorporating scalable data sources, especially human data with or without capture devices into our robotics foundation models.
• Leverage broader expertise to participate in a wide variety of research, including learning from simulation, reinforcement learning, learning from demonstrations, vision-language-action models, transformers, video generation, robot control, humanoid robots and more.
• Report and present research findings clearly and efficiently both internally and externally.

Minimum qualifications:

• PhD in Computer Science, a related field, or equivalent practical experience.
  
• 2 years of experience with reinforcement learning and imitation learning.
• Experience with vision, vision-language, video, and other multimodal models.
• Experience with multimodal generative modeling, training and inference.

Preferred qualifications:

• Experience with capture methodologies, dataset design, experimentation, and incorporation of captured human action data into VLAs or WAMs.
• Experience working with simulators and real-world robots, esp. dexterous manipulation, as well as multimodal sensing (e.g. tactile, forces).
• A passion for bringing research from the lab to real-world robotic systems.

• PhD in Computer Science, a related field, or equivalent practical experience.
  
• 2 years of experience with reinforcement learning and imitation learning.
• Experience with vision, vision-language, video, and other multimodal models.
• Experience with multimodal generative modeling, training and inference.