- DiscoverCustomersPartners
- Databricks PlatformIntegrations and DataPricingOpen Source
- Databricks for IndustriesCross Industry SolutionsMigration & DeploymentSolution Accelerators
- Training and CertificationEventsBlog and PodcastsGet HelpDive Deep
- CompanyCareersPressSecurity and Trust
- Ready to get started? GenAI Staff Machine Learning Engineer, AI Runtime San Francisco, California
- Design and productionize state of the art tooling and open source technologies to enable the development of frontier foundation models for Databricks customers
- Solve complex problems at scale around data preprocessing, model training, hyperparameter tuning and model evaluation
- Implement advanced optimization techniques to reduce the resource footprint of models while preserving their performance and balancing usability for our developers and customers
- Collaborate with product managers and cross-functional teams to drive technology-first initiatives that enable novel business strategies and product roadmaps
- Facilitate our user community through documentation, talks, tutorials, and collaborations
- Contribute to the broader AI community by publishing research, presenting at conferences, and actively participating in open-source projects, enhancing Databricks' reputation as an industry leader.
- Below are some example projects:
- : Large-scale distributed deep learning training library
- : Library for efficient data loading from cloud object storage
- : Framework for developing and evaluating Large Language Models
- Hands on experience with the internals of deep learning frameworks ( PyTorch, TensorFlow) and GenAI models ( GPT, StableDiffusion)
- Experience with large scale, distributed training on GPUs (, Nvidia, AMD) and alternative deep learning accelerators
- Strong sense of design and usability
- Effective communication skills and the ability to articulate complex technical ideas to cross-disciplinary internal and external stakeholders
- Prior history of contributing to or developing open source projects is a bonus but not a requirement
GenAI Staff Machine Learning Engineer, AI Runtime - San Francisco, United States - Databricks
Description
P-984
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.
You will:
We look for:
We value candidates who are curious about all parts of the company's success and are willing to learn new technologies along the way.
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 .