Databricks
GenAI Research Scientist, After-Training Team
Databricks, San Francisco, California, United States, 94199
Company DescriptionFounded in late 2020 by a small group of machine learning researchers, Mosaic AI enables companies to create state-of-the-art AI models from scratch on their own data. From a business perspective, 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. From a scientific perspective, Mosaic AI is committed to reducing the cost of training state-of-the-art models - and sharing our knowledge about how to do so with the world - to allow everyone to innovate and create models of their own.
Now part of Databricks since July 2023 as the GenAI Team, we are passionate about enabling our customers to solve the world's toughest problems by building and running the world's best data and AI platform. We leap at every opportunity to solve technical challenges, striving to empower our customers with the best data and AI capabilities.
Job DescriptionAs 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.
Specific to fine-tuning, RLHF, and after-training, you will build on the models we have pre-trained by making it possible for them to follow instructions, refining their behaviors to better address the needs of our users, and extending them to new capabilities like longer contexts, higher resolutions, tool use, etc. You will study the latest techniques in these areas, improve upon them to meet our needs, and generalize them to meet the needs of our customers.
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.
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Now part of Databricks since July 2023 as the GenAI Team, we are passionate about enabling our customers to solve the world's toughest problems by building and running the world's best data and AI platform. We leap at every opportunity to solve technical challenges, striving to empower our customers with the best data and AI capabilities.
Job DescriptionAs 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.
Specific to fine-tuning, RLHF, and after-training, you will build on the models we have pre-trained by making it possible for them to follow instructions, refining their behaviors to better address the needs of our users, and extending them to new capabilities like longer contexts, higher resolutions, tool use, etc. You will study the latest techniques in these areas, improve upon them to meet our needs, and generalize them to meet the needs of our customers.
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.
#J-18808-Ljbffr