RDQ427R276
Location: San Francisco or Seattle
At Databricks, we are passionate about enabling data teams 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 infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to tackle technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.
More about the team:
The AI Platform team builds the infrastructure that powers machine learning and AI at scale on Databricks. Our products span the full ML lifecycle — from feature engineering and model training to model serving and monitoring — enabling data and AI teams to build, deploy, and operate production ML systems with confidence. We work across some of the most technically demanding areas in the platform, including recommendation systems, real-time inference, large-scale distributed training, LLM infrastructure, vector search, and feature stores.
Our mission is to make it radically easier for enterprises to put AI into production. We do this by providing a unified, governed, and performant AI platform that integrates deeply with the Databricks Data Intelligence Platform — connecting MLflow, Unity Catalog, Model Serving, Vector Search, Feature Engineering, LLM, and Agent infrastructure into a cohesive experience. You will join a team that ships products used by thousands of the world's most sophisticated data and AI organizations.
You will drive the vision and roadmap for AI platform product areas and define how customers build, train, deploy, and monitor AI and ML systems on Databricks. You will collaborate across engineering teams to deliver an integrated and powerful path from experimentation to production.
The impact you will have:
- You will own the product roadmap for AI platform areas — defining what we build, why, and in what order — to accelerate customer adoption of AI and ML in production.
- You will drive strategy for key AI platform capabilities, shaping how enterprises operationalize AI at scale.
- You will partner closely with engineering teams to make deeply technical decisions about ML infrastructure — from distributed training architectures to real-time serving systems.
- You will represent the voice of the customer by engaging directly with enterprise ML teams, translating their pain points and workflows into platform capabilities that simplify the path to production AI.
- You will collaborate with GTM, Solutions Architecture, and Customer Success teams to drive enterprise adoption, shape field enablement, and inform competitive positioning.
- You will define pricing, packaging, and commercialization strategy for AI platform features, working with business teams to maximize value capture.
- You will grow end-user engagement with Databricks AI tools by identifying adoption bottlenecks and partnering cross-functionally to remove them.
What we look for:
- 5+ years of experience as a Product Manager working on platform or infrastructure products, ideally in ML/AI, data, or cloud services.
- Deep technical background — CS, EE, or equivalent degree strongly preferred; former software engineer experience is a significant plus. You should be comfortable going deep on system architecture, writing technical specs, and engaging credibly with world-class ML engineers.
- Experience with ML/AI infrastructure, data platforms, or cloud services (e.g., model training, model serving, feature stores, vector search, LLM infrastructure, ML pipelines, or similar systems). Familiarity with recommendation systems is a bonus.
- Proven enterprise B2B product management experience with highly technical customers — you have shipped platform products, driven commercial outcomes, and worked with field teams to land enterprise deals.
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 certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing 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.
Benefits
At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.
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.
Databricks Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Databricks and has not been reviewed or approved by Databricks.
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Equity Value & Accessibility — Equity grants and RSUs are a major part of total compensation and are highlighted for meaningful upside potential. Stock-based awards and refreshers contribute to strong overall pay positioning across senior technical and go-to-market roles.
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Healthcare Strength — Medical, dental, and vision coverage are complemented by mental-health resources, an EAP, and wellness reimbursements. Health benefits are consistently framed as comprehensive and competitive.
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Parental & Family Support — Paid parental leave for all parents, fertility support, and backup care options provide tangible assistance for family needs. Hybrid work norms and team-day structure further ease coordination for caregivers.
Databricks Insights
What We Do
As the leader in Unified Data Analytics, Databricks helps organizations make all their data ready for analytics, empower data science and data-driven decisions across the organization, and rapidly adopt machine learning to outpace the competition. By providing data teams with the ability to process massive amounts of data in the Cloud and power AI with that data, Databricks helps organizations innovate faster and tackle challenges like treating chronic disease through faster drug discovery, improving energy efficiency, and protecting financial markets.
