Engineering Manager - Mosaic AI Runtime

P-931

Founded in late 2020 by a small group of machine learning engineers and researchers, MosaicML enables companies to securely fine-tune, train and deploy custom AI models on their own data, for maximum security and control. Compatible with all major cloud providers, the MosaicML platform provides maximum flexibility for AI development. Introduced in 2023, MosaicML’s pretrained transformer models have established a new standard for open source, commercially usable LLMs and have been downloaded over 3 million times. MosaicML 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.

Now part of Databricks since July 2023, we are passionate about enabling our customers to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI platform so our customers can use deep data insights to improve their business. We leap at every opportunity to solve technical challenges, striving to empower our customers with the best data and AI capabilities.

Summary

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

We look for:

• 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.