PhD GenAI Research Scientist Intern
Job Summary
Job Description
At Databricks, we enable data teams to solve complex problems by building the world’s best data and AI platform. The Mosaic AI organization focuses on developing AI models and systems using proprietary data, including fine-tuning LLMs and building compound AI systems. This research role aims to advance "domain adaptation" for LLMs and AI systems in enterprise settings. Projects involve tackling open research problems like scaling evaluation, fine-tuning with synthetic data, retrieval augmentation, and efficient inference, contributing to new methods and recipes for post-training.
Must have:
- Push the frontier of domain adaptation for LLMs and AI systems
- Develop LLMs and AI systems that work well for custom enterprise domains
- Tackle open research problems on scaling/automating evaluation
- Fine-tune with synthetic data
- Implement retrieval augmentation
- Focus on fast/efficient inference
- Work on adapting, improving, and evaluating methods from literature
- Design new methods for domain adaptation
- Compose multiple methods to create new recipes for efficient post-training
- Evaluate LLMs and AI systems
- Research experience in and proficiency with the fundamentals of deep learning
- Pursuing a PhD in computer science or related fields
- Proficient software engineering skills, including with PyTorch
Perks:
- Comprehensive benefits and perks
4 skills required
Job Details
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.
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