Engineering Manager - Mosaic AI Runtime

Vollzeit
San Francisco, CA, USA
vor 6 Monate

P-1313

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.

 

Benefits

  • Medical, Dental, and Vision
  • 401(k) Plan
  • FSA, HSA and Commuter Benefit Plans
  • Equity Awards
  • Flexible Time Off
  • Paid Parental Leave 
  • Family Planning
  • Fitness Reimbursement
  • Annual Career Development Fund
  • Home Office/Work Headphones Reimbursement
  • Employee Assistance Program (EAP)
  • Business Travel Accident Insurance
  • Mental Wellness Resources

Pay Range Transparency

Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents base salary range for non-commissionable roles or on-target earnings for commissionable roles.  Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks utilizes the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.

 

Local Pay Range$192,000—$260,000 USD

About Databricks

Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.

Our Commitment to Diversity and Inclusion

At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.

Compliance

If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.