The Principal AI Research Scientist for AI Scaling at Databricks will lead a team focused on advancing large-scale machine learning, particularly in the areas of post-training, reinforcement learning, and inference efficiency. This role involves defining and executing a research roadmap that enhances the Databricks AI platform, ensuring improvements in how customers train and serve large language models. The position requires collaboration with product and engineering teams to translate research breakthroughs into impactful capabilities. The ideal candidate will foster a culture of scientific excellence and represent the organization in external forums.

• Proven ability to lead a research team to develop novel techniques for foundation model efficiency and related topics.
• Deep expertise in at least one of generative AI, LLMs, distributed ML systems, model optimization, or responsible AI.
• Strong programming skills and demonstrated ability to write high-quality, efficient code in Python and PyTorch.
• Demonstrated ability to translate research innovation into scalable product capabilities.
• Excellent communication, leadership, and stakeholder management skills.

• Lead and grow a multidisciplinary research team focused on foundational and applied AI problems.
• Define the scaling research roadmap in alignment with Databricks’ strategic objectives.
• Drive algorithmic innovations for large-scale neural network training and inference.
• Optimize end-to-end ML systems for distributed training and reinforcement learning.
• Partner with product and engineering to translate research breakthroughs into customer-impacting capabilities.
• Mentor and develop talent, providing technical guidance and career development support.