Senior Machine Learning Engineer - GenAI Platform
Databricks · San Francisco, CA · Engineering - Pipeline
About this role
Databricks is hiring a senior-level ML Platform Engineer in the machine learning function based in San Francisco, CA. The posting calls out experience with Python, Scala, Spark, Databricks. Compensation is listed at $166,000–$225,000 per year.
- Role
- ML Platform Engineer
- Function
- machine learning
- Level
- senior
- Track
- Individual contributor
- Employment
- Full-time
- Location
- San Francisco, CA
- Department
- Engineering - Pipeline
More roles at Databricks
Job description
from Databricks careersP-984
Founded in late 2020 by a small group of machine learning engineers and researchers, Mosaic AI 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 Mosaic AI platform provides maximum flexibility for AI development. Introduced in 2023, Mosaic AI’s pretrained transformer models have established a new standard for open source, commercially usable LLMs and have been downloaded over 3 million times. 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.
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:
Databricks Mosaic AI is hiring experienced machine learning platform engineers to build out our customer-facing generative AI platform for the ML development lifecycle including data generation, training, evaluation, serving, and agent-building.