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Principal AI Research Scientist, Research Director - AI Scaling
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ICT
💰 Salary Not shared
📊 Market NA
About the Company
At Databricks, we are obsessed with enabling data teams to solve the world's toughest problems, from security threat detection to cancer drug development, by building and running the world's best data and AI platform. The Databricks AI Research organization enables companies to develop AI models and agents using their own data, with technologies ranging from post-training open source LLMs to developing advanced multi-agent architectures. Databricks AI is committed to the belief that a company's AI models and agents are just as valuable as any other core IP, and that high-quality AI should be available to all. The Databricks AI Scaling team focuses on pushing the boundaries of large language model (LLM) training and inference efficiency beyond what is required to support existing models. The team explores novel avenues for scaling and efficiency improvements across algorithms, systems, and infrastructure, requiring researchers who can both drive independent research agendas and dive deep into low level implementation details with engineering partners.
Responsibilities
- ● Lead and grow a multidisciplinary research team focused on foundational and applied AI problems, with a particular emphasis on LLM scaling, efficiency, and systems performance.
- ● Define the scaling research roadmap in alignment with Databricks' strategic objectives, prioritizing advances in foundation model efficiency and large scale training and inference.
- ● Drive algorithmic innovations for large scale neural network training and inference, including novel optimizers, low precision techniques, and model adaptation methods, and guide your team in rigorous empirical validation against state of the art approaches.
- ● Optimize end to end ML systems for distributed training and RL, memory efficiency, and compute efficiency through close collaboration with core systems and platform teams, ensuring that research ideas translate into performant, reliable infrastructure.
- ● Partner with product and engineering to translate research breakthroughs, especially around scaling and efficiency, into customer impacting capabilities in the Databricks AI platform.
- ● Foster a culture of scientific excellence and openness, including high quality research practices, reproducible experimentation, and effective internal knowledge sharing across Databricks AI.
- ● Represent Databricks AI research externally through top tier publications, conference talks, and collaborations with academia and the open source community, with a focus on optimization and efficiency for large scale models.
- ● Mentor and develop talent, providing both technical guidance (research agendas, experimentation, implementation) and career development support for research scientists and engineers.
- ● Define and lead independent research programs on foundation model efficiency, covering topics such as o
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