Field Engineering, Mosiac AI Product Specialist

FEQ125R71

While candidates in the listed locations are encouraged for this role, we are open to remote candidates in other locations.

The Product Specialist for Generative AI will lead the enablement, expertise, and backline support for our customer-facing field team for Generative AI. This will include supporting RAG (retrieval augmented generation) POCs, open source models like Llama2, MPT, Mistral, DBRX and fine-tuning and pre-training custom models as well as using 3rd party models including OpenAI, Anthropic or Mistral. Knowledge of Vector Indexing and Distributed Pytorch is a plus.

You will represent the product internally to our field engineering teams, and externally to the market via speaking at conferences, online webinars, and blog posts. You will meet with customers to communicate the vision and gather feedback.

You will not have any direct reports but will recruit, lead, encourage, and reward a group of specialists across the field dedicated to enable Generative AI use cases on Databricks.

You have expertise in Data Science, Machine Learning, Generative AI, NLP and Computer Vision and expertise in using PySpark and SQL. You will excel in distilling product features into a compelling value proposition and enabling Account Executives and Field Engineers to communicate the value in a way through content and demonstrations.

The impact you will have:

• Be a technical expert on all aspects of the Mosaic AI family of products with awareness for the Databricks Data Intelligence Platform and the broader ecosystem
• Work hands-on with deeply technical customers as the engineering/research liaison to demonstrate and communicate Databricks’ GenAI products and value
• Embed and partner closely with the Mosaic AI engineering and research teams and be an extension of them when interfacing with customers and prospects
• Dive into a customer’s code to help them get going on the product(s) or unstick them so they can get started
• Create and execute compelling demos to showcase Mosaic AI to specific customer’s industries and use cases by compiling data sets, data wrangling, model training, and communicating results
• Support your customers by assisting with initial model scoping and creation
• Partner closely with sales and other Mosaic AI leaders to grow thought leadership and drive customer success
• Proactively automate tasks as needed and partner closely with the product, engineering, and research teams to be their eyes and ears in the field and bring back information and ideas to drive the products forward
• Be comfortable with defining customer requirements and definitions - building demos, assisting with proposals, solution briefs, and bringing in professional services when needed
• Strive in uncomfortable situations with ambiguity and uncertainty in the best way to help solve customer problems
• Work with sales and other stakeholders, including partners to jointly define solutions
• Participate in pre-sales on-site visits and be the go-to technical point person for initial customer interaction

What we look for:

• 10+ years of engineering and pre-sales customer facing experience
• ML experience as either an engineer or researcher
• Strong software engineering skills with expertise in Python
• Experience in a fast-paced, entrepreneurial environment
• Expertise with enterprise cloud environments (AWS, Azure, GCP, OCI), technologies (e.g., kubernetes, containers), and the ML focused hardware accelerators (Nvidia A100s and H100s, AMD MI series, etc.)
• Experience with Mosaic Composer and other ML technologies and frameworks (e.g., PyTorch)
• Outstanding skills in presenting to both technical and executive audiences, whether impromptu on a whiteboard or using presentations and demos
• Strong aptitude and willingness to learn and excel in new technologies and push the envelope of what is possible
• Strong verbal and written communication skills and ability to lead effectively across organizations both internally and with customers
• ​​A minimum of a bachelor's degree in Computer Science, Information Systems, Engineering, Data Science, or equivalent experience through demonstrable work experience
• Nice to have: experience in fast growing startups in the AI space with a focus on GenAI, NLP, CV, and diffusion models.

Benefits:

• 401(k) Plan

• Equity awards

• Flexible time off

• Paid parental leave

• Family Planning

• Gym reimbursement

• Annual personal development fund

• Employee Assistance Program (EAP)

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.

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.

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.