The Principal Research Scientist – Scaling at Databricks will lead a team of researchers and engineers to enhance large-scale machine learning, particularly focusing on post-training, reinforcement learning, and inference efficiency. The role involves defining a research roadmap that aligns with Databricks' strategic objectives and delivering improvements in how customers train and serve large language models. The Scaling Research Team is dedicated to exploring novel methods for scaling and efficiency in AI models. This position requires collaboration with product and engineering teams to translate research into impactful capabilities.

• Proven ability to lead a research team to develop novel techniques for foundation model efficiency and related topics.
• Deep expertise in generative AI, large language models, distributed ML systems, model optimization, or responsible AI.
• Strong programming skills in Python and PyTorch for research implementation and experimentation.
• 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.
• Foster a culture of scientific excellence and openness within the team.
• Represent Databricks AI research externally through publications and conference talks.
• Mentor and develop talent within the research team.