onsite
Sr. Research Scientist, AI Research, Scaling Team
Sr. Research Scientist, AI Research, Scaling Team
As a Sr. Research Scientist on the AI Research Scaling team at Databricks, you will advance the scientific frontier in deep learning and foundation model efficiency. You will define and lead independent research agendas, drive algorithmic innovations for large-scale neural networks, and optimize ML systems for distributed training and efficiency through hands-on implementation.
About the role
Job Description
As a Sr. Research Scientist on the Scaling team, you will be responsible for keeping up with the latest developments in deep learning and advancing the scientific frontier by creating new techniques that go beyond the state of the art. You will work together on a collaborative team of researchers and engineers with diverse backgrounds and technical training. And most importantly, you will love our customers: our goal is to make our customers successful in applying state-of-the-art LLMs and AI systems, and we encode our scientific expertise into our products to make that possible.
The Impact you will have
As a Sr. Research Scientist on the AI Research Team at Databricks, You Will:
- Define and lead independent research agendas on foundation model efficiency in model training and reinforcement learning, conducting experiments to empirically validate hypotheses and benchmark against state-of-the-art approaches
- Drive algorithmic innovations for large-scale neural network training or inference (e.g., novel optimizers, low-precision techniques, model adaptation methods)
- Optimize ML systems for distributed training, memory efficiency, and compute efficiency through hands-on implementation.
What We Look for
- MS/PhD in Computer Science or related field with strong foundations in machine learning and systems
- Proven ability to write high-quality, efficient code in Python and PyTorch for research implementation and experimentation
- Strong preference for candidates with first-author publications at top ML/systems conferences (ICLR, ICML, NeurIPS, MLSys) focused on optimization or efficiency.
Skills
Deep LearningPythonPyTorchMachine LearningDistributed Trainingmemory efficiencycompute efficiencyneural network trainingInferenceoptimizerslow precision techniquesmodel adaptation methodsReinforcement Learning