At Databricks, we are obsessed with enabling data teams to solve the world’s toughest problems, from security threat detection to cancer drug development. We do this by building and running the world’s best data and AI platform so our customers can focus on the high-value challenges that are central to their own missions. The Mosaic AI organization enables companies to develop AI models and systems using their own data, with technologies ranging from pre-training LLMs from scratch to augmented generation using the latest retrieval techniques. Mosaic AI does so by producing novel science and putting it into production. Mosaic AI is committed to the belief that a company’s AI models are just as valuable as any other core IP, and that high-quality AI models should be available to all.

Drive performance improvements through advanced optimization techniques including kernel fusion, mixed precision, memory layout optimization, tiling strategies, and tensorization for training-specific patterns

Design, implement, and optimize high-performance GPU kernels for training workloads (e.g., attention mechanisms, custom layers, gradient computation, activation functions) targeting NVIDIA architectures

Design and implement distributed training frameworks for large language models, including parallelism strategies (data, tensor, pipeline, ZeRO-based) and optimized communication patterns for gradient synchronization and collective operations

Profile, debug, and optimize end-to-end training workflows to identify and resolve performance bottlenecks, applying memory optimization techniques like activation checkpointing, gradient sharding, and mixed precision training.