USD per year
Senior Machine Learning Engineer - GenAI Platform
San Francisco, California Apply now P-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. You will thrive in this role if you have a strong sense of end-to-end ownership and enjoy translating user requirements into product interfaces and building the backend distributed systems to power those interfaces. In this role, you will have the opportunity to contribute to all areas of our stack spanning from user-facing features to low-level GPU orchestration. You will:
- Play a key role in the end-to-end design and implementation of our product which is a platform for powering use cases across training and serving of generative AI models
- Work closely with both customers and internal ML researchers to identify key areas of development for our generative AI platform
- Have strong end-to-end product ownership, translating product requirements into user interfaces and backend distributed system design and own end-to-end implementation
- Design and build the core platform infrastructure that supports our customer-facing product features
- Ensure the reliability, security, and scalability of the backend distributed systems that power all aspects of our product
We look for:
- 4+ years of hands-on programming experience with at least one modern language such as Python, Scala, Go, or C++
- Strong sense of distributed systems design and experience building large-scale systems
- Experience building ML platform systems for applications in the ML model development lifecycle such as data preparation, model training, model evaluation, and model serving
- Direct experience developing ML models is a plus but not required
- Strong sense of end-to-end product ownership as well as intuition for both robust system design and product usability
- Effective communication skills and the ability to articulate complex technical ideas to cross-disciplinary internal and external stakeholders.
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 the expected 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 certificationsand training,and specific work location. Based onthe factors above,Databricks anticipates utilizingthe full widthofthe range.The total compensation package for this position may also include eligibility for annual performance bonus,equity,andthe benefits listed above.For more information regarding which range your location is in visit our page here. Local Pay Range $166000$225000 USD About Databricks Databricks is the dataand AI company.More than 10000 organizations worldwide — including Comcast,Cond Nast,Grammarly,and over 50% ofthe Fortune500 — rely onthe Databricks Data Intelligence Platformto unifyand democratize data,analyticsand AI.Databricks is headquartered in San Francisco,with offices aroundthe globeand was founded bythe original creators of Lakehouse,Apache Spark™,Delta Lakeand MLflow.To learn more,follow Databricks on Twitter,LinkedInand Facebook. Benefits At Databricks,we strive to provide comprehensive benefitsand perks that meetthe needs of all of our employees.For specific details on the benefits offered in your region,please visit https://www.mybenefitsnow.com/databricks. Our Commitment to Diversity and Inclusion At Databricks,we are committed to fostering a diverseand inclusive culture where everyone can excel.We take great care to ensure that our hiring practices are inclusiveand meet equal employment opportunity standards.Individuals looking for employment at Databricks are considered without regard to age,olor, isability,ethnicity,family or marital status,gender identity or expression,languagenational originphysical or mental abilitypolitical affiliationrace,religionsexual 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.
Databricks is a data and AI company that unifies data engineering, analytics, and machine learning on a lakehouse architecture. Founded by the original creators of Apache Spark, it offers a cloud-based platform for building, deploying, and maintaining enterprise-grade data and AI solutions at scale.
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