AWS, Azure, Effective communication skills, Google Cloud Platform (GCP), Large Language Models - LLMs, Machine learning techniques, Natural Language Processing (NLP)
While candidates in the listed locations are encouraged for this role, we are open to remote candidates in other locations.
The Machine Learning (ML) Practice team is a specialized customer-facing ML team at Databricks facing an increasing demand for Large Language Model (LLM)-based solutions. We deliver professional services engagements to help customers build and improve ML pipelines, and put those pipelines into production. We work with customers to help them shape their long-term initiatives working alongside engineering, product, and developer relations, and internal subject matter expert (SME) teams. The ideal candidate will enjoy being part of a broader team of technologists that love empowering customers, collaborating with teammates, and satisfying your curiosity working with the latest trends in LLMs, MLOps, and ML.
The impact you will have:
What we look for:
Benefits
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.
Zone 1 Pay Range
$124,800—$220,800 USD
Databricks is an American enterprise software company founded by the creators of Apache Spark. Databricks develops a web-based platform for working with Spark, that provides automated cluster management and IPython-style notebooks. Databricks grew out of the AMPLab project at University of California, Berkeley that was involved in making Apache Spark, an open-source distributed computing framework built atop Scala.
San Francisco, CA, USA
4-6 year
San Francisco, CA, USA
4-6 year
Mumbai, Maharashtra, India
6-8 year
United States
6-8 year
United States
6-8 year
United States
6-8 year
United States
6-8 year
Washington D.C., DC, USA
6-8 year
Los Angeles, CA, USA; Portland, OR, USA; Sacramento, CA, USA; San Diego, CA, USA; San Francisco, CA, USA; San Jose, CA, USA; Seattle, WA, USA
4-6 year
San Francisco, CA, USA
8-10 year
San Francisco, CA, USA
0-2 year
Bengaluru, Karnataka, India
2-4 year
Bengaluru, Karnataka, India
2-4 year
Amsterdam, Netherlands
0-2 year