Synced from Greenhouse · Jul 1

GenAI Research Scientist

DatabricksSan Francisco, CaliforniaPosted Jul 1, 2026
Research ScientistIntern
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Mirrored from Databricks's own Greenhouse careers system · refreshed hourly

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Jul 1
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Greenhouse
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Job descriptionReq 7011263002

Company Description:

At Databricks, we are obsessed with enabling data teams to solve the world’s toughest problems, from security threat detection to cancer drug development. We do this by building and running the world’s best data and AI platform, so our customers can focus on the high value challenges that are central to their own missions.

The Mosaic AI organization enables companies to develop AI models and systems using their own data, with technologies ranging from fine-tuning LLMs for enterprise domains, to a platform for building compound AI systems that use retrieval and agents. Mosaic AI is committed to the belief that a company’s AI models are just as valuable as any other core IP, and that high-quality AI models should be available to all.

Job description:

Most of the world's data+AI problems lie in enterprise domains, behind closed doors. Our research team's goal is to push the frontier of "domain adaptation" - how can we develop LLMs and AI systems that work well for custom domains. To do this we are tackling open research problems on a range of topics, from how to scale/automate eval, fine tune with synthetic data, retrieval augmentation, fast/efficient inference and more. 

You will work with our research team on projects focused on adapting LLMs and AI systems towards enterprise domains. This may include:

  • Adapting, improving, and evaluating a method from the literature.
  • Designing an entirely new method for domain adaptation.
  • Composing together multiple methods to create new recipes for efficient post-training.
  • Evaluation of LLMs and AI systems. 

Your qualifications and qualities:

  •  Required:
    • Research experience in and proficiency with the fundamentals of deep learning.
    • Pursuing a PhD in computer science or related fields (electrical engineering, neuroscience, physics, math, etc.).
    • Proficient software engineering skills, including with PyTorch.

 

Pay Range Transparency

Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles.  Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.

 

SF Bay Area Hourly Rate
$54—$60 USD

About Databricks

Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.

Benefits

At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.

Our Commitment to Diversity and Inclusion

At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.

Compliance

If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.

View original posting on Greenhouse

What applying to Databricks usually looks like

Based on publicly available information, candidates applying through greenhouse for roles at Databricks can generally expect a structured process typical of this ATS. This commonly begins with an online application and resume screen, followed by a recruiter conversation to discuss background and role fit. Depending on the position, candidates may encounter technical assessments, take-home exercises, or case studies, particularly for engineering, data, and analytical roles. The process may include multiple stages such as hiring manager conversations, panel discussions, and team or cross-functional interviews. Response times vary and communication is typically managed through the greenhouse platform, including scheduling and status updates. Candidates should prepare to discuss relevant experience, technical skills, and role-specific scenarios, as greenhouse-based processes commonly emphasize structured evaluation criteria across candidates to support consistent, comparative hiring decisions throughout the pipeline.

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GenAI Research Scientist
Databricks · San Francisco, California
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