The MosaicAI Runtime team develops and maintains the LLM Foundry, Composer, and StreamingDatasets open source projects, which power deep learning training for Databricks customers and MosaicAI Research. We're hiring an Engineering Manager to help build our products and develop our team of machine learning engineers. Your mission will be to establish the MosaicAI Runtime as the leading deep learning training framework for Databricks customers and the community. This will involve adding support for cutting-edge models and training techniques, creating a user-friendly experience, and enabling customers and partners to utilize state-of-the-art generative models for their business needs.

You will:

Directly manage a team of software development engineers: assigning and reviewing work, evaluating performance, providing feedback, and mentoring for career development

Oversee and audit the design and implementation of the deep learning training software developed by the team

Establish software development best practices, and lead by example in applying them

Develop the broader engineering organization and culture through hiring, mentoring, and feedback

Drive roadmap planning, execution, and coordination across functions: other engineering teams, research, customer support, marketing, and sales

2+ years of experience managing software development engineers developing ML systems and/or services

4+ years of hands-on experience with the internals of deep learning frameworks (e.g. PyTorch, TensorFlow) and GenAI models (e.g. GPT, StableDiffusion)

4+ years of experience contributing to the architecture and design of large scale distributed training on GPUs (e.g., Nvidia, AMD) and alternative deep learning accelerators

Strong sense of software design and usability of ML systems

Experience applying software engineering methodologies and best practices including coding standards, code reviews, build processes, testing, and security.

Prior history of contributing to or developing open source projects is a bonus but not a requirement

We value candidates who are curious about all parts of the company's success and are willing to learn new skills and technologies along the way.