GenAI Research Scientist at Databricks

GenAI Research Scientist

Research Scientist on the GenAI Team at Databricks will advance the scientific frontier by creating new techniques for large language models.

As a Research Scientist on the GenAI Team at Databricks, you will be responsible for keeping up with the latest developments in deep learning and advancing the scientific frontier by creating new techniques that go beyond the state of the art. You will work together on a collaborative team of researchers with diverse backgrounds and technical training. And most importantly, you will love our customers: our goal is to make our customers successful when they train large models, and we encode our scientific expertise into our products to make that possible.

You might be a good fit if you…

Are comfortable working with large-scale LLMs in the 10s to 100s of billions of parameters.
Have solid ML and RL software engineering and scientific research skills.
Have produced novel research related to fine-tuning LLMs or improving upon pre-trained LLMs.
Have specialized expertise in topics like fine-tuning, RLHF, LLM tool-use, etc.
Are passionate about getting your work into the hands of real users and - more broadly - democratizing access to modern AI technology.
Are motivated by working on LLM research that - contrary to the general trend in the field - will be disclosed to the public.
Have strong communication skills and a desire to work on a small, fast-paced team.

A PhD is NOT required for this role. We are open to hiring candidates with bachelor's and master's degrees and to new graduates. We are open to hiring candidates who are currently in "research engineer" roles at other companies.

Your Responsibilities

Keeping up to date with the research literature and thinking beyond the state of the art to address the needs of our users.
Developing and implementing methods that extend and improve model capabilities, reliability, and safety.
Rigorously evaluating these methods, communicating the results of your findings, and putting those that are useful into production.

Pay Range Transparency

Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents base 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 utilizes 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.

Local Pay Range

$150,000—$190,000 USD

You might be a good fit if you…

Are comfortable working with large-scale LLMs in the 10s to 100s of billions of parameters.

Have solid ML and RL software engineering and scientific research skills.

Have produced novel research related to fine-tuning LLMs or improving upon pre-trained LLMs.

Have specialized expertise in topics like fine-tuning, RLHF, LLM tool-use, etc.

Are passionate about getting your work into the hands of real users and - more broadly - democratizing access to modern AI technology.

Are motivated by working on LLM research that - contrary to the general trend in the field - will be disclosed to the public.

Have strong communication skills and a desire to work on a small, fast-paced team.

Your Responsibilities

Keeping up to date with the research literature and thinking beyond the state of the art to address the needs of our users.

Developing and implementing methods that extend and improve model capabilities, reliability, and safety.

Rigorously evaluating these methods, communicating the results of your findings, and putting those that are useful into production.

Pay Range Transparency

Local Pay Range

$150,000—$190,000 USD