USD 147,000–210,000/yearAnnual period assumed — pay source
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $147000 - $210000 (USD) + 15% bonus target + equity + benefits
Learn more aboutbenefits at Google (https://www.google.com/about/careers/applications/benefits/) .
PhD in Computer Science or a related field, or equivalent practical experience
Experience with robot policy learning such as imitation learning or RL on simulators and real robots
Experience working with simulators and robots
Publications at conferences such as NeurIPS, CoRL, ICML, or ICLR
Qualification wording
PhD in Computer Science, a related technical field, or equivalent practical experience.
Experience working with robot policy learning (e.g., imitation learning, RL) across simulators and real-world robotic platforms
Experience working with simulators and robots.
Experience contributing to research communities or efforts, including publishing papers at conferences (e.g., NeurIPS, CoRL, ICML, ICLR).
Education & alternatives
**Minimum qualifications:**
+ PhD in Computer Science, a related technical field, or equivalent practical experience.
+ Experience working with robot policy learning (e.g., imitation learning, RL) across simulators and real-world robotic platforms (e.g., dexterous manipulation, multimodal sensing).
Actively hiringFirst seen by us 11 days ago, still listed, and not a repost of an earlier posting.
Status in our records
Live
First seen by us
Oct 31, 202611 days ago
Recorded sightings
8
Last seen by us
Nov 10, 2026
Employer says posted
Oct 28, 2026
Oct 31, 2026today
We found this posting on the National Labor Exchange. These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Pay
In line with similar jobs
$118K$195K
$147K–$210K against $118K–$195K, the middle half of what similar US postings state.
From 3,817 postings in the last year. Stated ranges, not salaries paid.
Time since we first saw it
Day 11
859
Similar jobs usually come down between day 8 and day 59.
Well past Google’s usual: its jobs come down by about day 3.
From 11,414 similar postings that came down, and 484 of Google’s. Coming down is not always a hire.
Google is hiring
233 open jobs
Open jobs by the week we first saw them, last 12 weeks.
About 190,820 in 2025, up 4% from the year before.Annual report (SEC Form 10-K)
Company
Listed as GOOGL.
H-1B visas
1,765 approved for new hires in fiscal 2025.US Citizenship and Immigration Services
Demand for Data Scientist roles
New Data Scientist postings at the employers we follow are down 6% over the last 6 weeks compared with the 6 before.
August 17Last week
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under Data Scientist, by the work the posting describes.
Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.
Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.
Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.
Research Scientist, Robotics Data, Pretraining, DeepMind
Share Research Scientist, Robotics Data, Pretraining, DeepMind
_corporate_fare_ DeepMind _place_ Mountain View, CA, USA
Share Research Scientist, Robotics Data, Pretraining, DeepMind
**Minimum qualifications:**
+ PhD in Computer Science, a related technical field, or equivalent practical experience.
+ Experience working with robot policy learning (e.g., imitation learning, RL) across simulators and real-world robotic platforms (e.g., dexterous manipulation, multimodal sensing).
+ Experience working with simulators and robots.
+ Experience contributing to research communities or efforts, including publishing papers at conferences (e.g., NeurIPS, CoRL, ICML, ICLR).
**Preferred qualifications:**
+ Experience with systematic benchmarking, multimodal data sources, data labeling strategies, and data mixture optimization for frontier or robotics foundation models.
+ Practical experience in "hill-climbing" model performance (e.g., iteratively improving data curation, training recipes, and model benchmarks).
+ Proven ability to build and maintain clean research software and tools for rapid iteration on research ideas.
+ A passion for bringing foundation model research from the lab to robust, real-world robotic systems.
**About the job**
As 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.
As 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.
Our 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.
Artificial 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.
We 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.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $147000 - $210000 (USD) + 15% bonus target + equity + benefits
Learn more aboutbenefits at Google (https://www.google.com/about/careers/applications/benefits/) .
**Responsibilities**
+ Develop data quality, filtering, and labeling methodologies, and optimize multimodal data representations and mixtures to upstream physical and action knowledge into Gemini pre-training.
+ Design and run pre-training and policy training ablations, improve training recipes, and systematically hill-climb physical reasoning and action performance against benchmarks.
+ Build 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.
+ Contribute 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.
Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google'sApplicant and Candidate Privacy Policy (./privacy-policy) .
Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See alsoGoogle's EEO Policy (https://www.google.com/about/careers/applications/eeo/) ,Know your rights: workplace discrimination is illegal (https://careers.google.com/jobs/dist/legal/EEOC\_KnowYourRights\_10\_20.pdf) ,Belonging at Google (https://about.google/belonging/) , andHow we hire (https://careers.google.com/how-we-hire/) .
If you have a need that requires accommodation, please let us know by completing ourAccommodations for Applicants form (https://goo.gl/forms/aBt6Pu71i1kzpLHe2) .
Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.
To all recruitment agencies: Google does not accept agency resumes. Please do not forward resumes to our jobs alias, Google employees, or any other organization location. Google is not responsible for any fees related to unsolicited resumes.
Equity is granted exclusively and discretionarily by Alphabet Inc. on the basis of an agreement concluded between you and Alphabet Inc. Alphabet Inc. is your sole contractual partner with respect to equity grants. GSU grants are not guaranteed, are discretionary, are subject to approval by the Alphabet Inc. board of directors or its delegate, the terms of the relevant Alphabet Inc. stock plan, and your grant agreement. They have no impact on statutory payments. Current or past grants do not confer an acquired right.
Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also https://careers.google.com/eeo/ and https://careers.google.com/jobs/dist/legal/OFCCP_EEO_Post.pdf If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form: https://goo.gl/forms/aBt6Pu71i1kzpLHe2.
Selected passages from the saved posting. Check the full description for conditions and exceptions.
Pay
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $147000 - $210000 (USD) + 15% bonus target + equity + benefits
Learn more aboutbenefits at Google (https://www.google.com/about/careers/applications/benefits/) .
Location & working pattern
Mountain View, CA
Working pattern and location restrictions need checking in the full posting.
Work authorization
This passage needs a closer read in the full description.