{"id":3323717,"url":"https://alion.io/job/google-deepmind-research-scientist-robotics-data-pretraining","title":"Research Scientist, Robotics Data, Pretraining","company":{"id":4,"name":"Google DeepMind","domain":"deepmind.google","url":"https://alion.io/company/deepmind","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Career site","truth_index":null},"role":"Robotics","role_family":"Robotics","seniority":null,"employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Mountain View, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":147000,"max_usd":355000,"period":"year","method":"role_country_seniority_unknown","sample_n":590},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Gemini","optional":false},{"name":"Imitation Learning","optional":false},{"name":"Multimodal AI","optional":false},{"name":"Post-training","optional":false},{"name":"Pre-training","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"Vision-Language-Action","optional":false}],"status":"live","first_seen_at":"2026-10-27T07:38:52Z","employer_posted_date":"2026-10-27","last_verified_at":"2026-10-28T11:50:45Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"About the job\nAs an organization, Google maintains a portfolio of research projects driven by fundamental research, new product innovation, product contribution and infrastructure goals, while providing individuals and teams the freedom to emphasize specific types of work. As a Research Scientist, you'll setup large-scale tests and deploy promising ideas quickly and broadly, managing deadlines and deliverables while applying the latest theories to develop new and improved products, processes, or technologies. From creating experiments and prototyping implementations to designing new architectures, our research scientists work on real-world problems that span the breadth of computer science, such as machine (and deep) learning, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more.\nAs a Research Scientist, you'll also actively contribute to the wider research community by sharing and publishing your findings, with ideas inspired by internal projects as well as from collaborations with research programs at partner universities and technical institutes all over the world.\nOur mission is to combine Gemini foundation models with physical intelligence so general-purpose robots can understand and act reliably in the real world. Critical to achieving this goal is obtaining high-quality training data and effectively integrating it into the Gemini training process. Our team's research develops data quality insights on how to best extract physical and action knowledge from robot-related datasets, and incorporates these insights into Gemini pre-training through model training and upstreaming. By pairing data ablations with fast closed-loop robot evaluations, you will shape how physical reasoning and action capabilities emerge in next-generation Gemini models and deploy onto real-world robots.\nArtificial intelligence will be one of humanity’s most transformative inventions. At Google DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority.\nWe are pushing the boundaries across multiple domains. Our global teams offer diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.\nIndividual pay is determined by factors including job-related skills, experience, and relevant education or training.US: $147000 - $210000 (USD) + 15% bonus target + equity + benefits\nLearn more about benefits at Google.\nResponsibilities\nDevelop data quality, filtering, and labeling methodologies, and optimize multimodal data representations and mixtures to upstream physical and action knowledge into Gemini pre-training.\nDesign and run pre-training and policy training ablations, improve training recipes, and systematically hill-climb physical reasoning and action performance against benchmarks.\nBuild and maintain the research software, evaluation tools, and lightweight post-training workflows required to iterate on research ideas quickly and verify upstream data quality through offline and closed-loop robot policy evaluations.\nContribute to our wider research agenda-including vision-language-action (VLA) modeling, world-action models, reinforcement learning, and simulation-and communicate findings clearly in a fast-paced, collaborative team environment.\nQualifications\nMinimum qualifications:\nPhD in Computer Science, a related technical field, or equivalent practical experience.\nExperience working with robot policy learning (e.g., imitation learning, RL) across simulators and real-world robotic platforms (e.g., dexterous manipulation, multimodal sensing).\nExperience working with simulators and robots.\nExperience contributing to research communities or efforts, including publishing papers at conferences (e.g., NeurIPS, CoRL, ICML, ICLR).\nPreferred qualifications:\nExperience with systematic benchmarking, multimodal data sources, data labeling strategies, and data mixture optimization for frontier or robotics foundation models.\nPractical experience in \"hill-climbing\" model performance 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