Databricks PhD GenAI Research Intern | SF Bay · $54–60/hr Newer internship

Edubard; San Francisco, Northern (CA, KY); Hybrid; USD 74,000 - 83,000; Full time

Job summary

Databricks Mosaic AI Research is offering a PhD GenAI Research Scientist Intern position focused on enterprise domain adaptation for LLMs. Work includes evaluation, synthetic data, RAG, and efficient inference alongside the research team, using PyTorch.

The role calls for pursuing a PhD in CS or related fields, strong DL fundamentals, and solid software engineering skills with PyTorch, plus interest in applied research on real enterprise data.

Qualifications

• Pursuing a PhD in computer science or related field (EE, neuroscience, physics, math, etc.).
• Research experience and proficiency with deep learning fundamentals.
• Strong software engineering, including PyTorch.
• Interest in eval, fine-tuning, retrieval, agents, or efficient inference.
• Comfort working on applied research that has to work on real enterprise data.

Responsibilities

• Collaborate with Mosaic AI Research to develop domain adaptation methods for LLMs in enterprise settings.
• Design experiments and evaluate LLMs using PyTorch.
• Develop synthetic data pipelines and evaluate retrieval-augmented generation (RAG).

Skills

Deep learning fundamentals

Research experience

Software engineering

Domain adaptation

Evaluation & retrieval

Education

Pursuing PhD in CS or related field

Tools

PyTorch

Job description

• Role: PhD GenAI Research Scientist Intern
• Team: Mosaic AI Research
• Pay: $54–$60/hr (SF Bay)
• Focus: Enterprise domain adaptation for LLMs — eval, synthetic data, RAG, efficient inference

Overview

Databricks Mosaic AI helps companies build models on their own data. This PhD research internship works on “domain adaptation”: making LLMs and AI systems actually work in enterprise settings. You might adapt a paper method, design a new one, compose post-training recipes, or evaluate LLMs — alongside the research team, in PyTorch.

Key Requirements

• Pursuing a PhD in computer science or a related field (EE, neuroscience, physics, math, etc.)
• Research experience and proficiency with deep learning fundamentals
• Strong software engineering, including PyTorch
• Interest in eval, fine-tuning, retrieval, agents, or efficient inference
• Comfort working on applied research that has to work on real enterprise data