Senior / Staff Product Manager - Ray Data

Cerebras; Palo Alto (CA); On-site; USD 120,000 - 160,000; Full time

Job summary

A leading AI technology company is seeking a Senior Product Manager for their Ray Data scalable data processing library. This role involves driving product strategy while balancing open-source growth and commercial differentiation. Candidates should have over 3 years in product management, a solid technical background in distributed systems, and experience engaging with both developers and enterprise customers. This position offers opportunities to shape the future of AI data processing, working in a dynamic environment located in the Bay Area.

Qualifications

• 3+ years of product management experience with technical products.
• Strong technical background in distributed systems, ML infrastructure, or data processing.
• Strategic thinking with ability to balance competing priorities and stakeholder needs.

Responsibilities

• Drive the Ray Data product roadmap while ensuring balance between open source and commercial products.
• Focus on community growth and ecosystem integrations for Ray Data.
• Work with Product Marketing on market positioning and competitive analysis.
• Assist sales and field engineering teams in customer engagements.

Skills

Product management experience

Technical background in distributed systems

Experience with developer and enterprise audiences

Strategic thinking

Job description

About the Role

Anyscale is seeking a Senior Product Manager to lead Ray Data, our scalable data processing library for ML and AI workloads.

This is a uniquely challenging role that requires balancing open source growth with commercial differentiation - driving rapid adoption in the open source Ray Data ecosystem while building compelling proprietary features for RayTurbo Data, our high-performance commercial engine.

You'll own the entire Ray Data product roadmap in a competitive landscape, working closely with the engineering team, the field team, enterprise customers, and the open source community. Success requires:

• Deeply ingraining yourself into the end-user experience to understand the nature of the product and its gaps and tradeoffs

• Working closely with customers and open source users to draw the subtle line between growth and commercialization

• Strategic thinking about which parts of the ML/Data lifecycle to focus on, identifying opportunities where our architectural strengths create the most value.

• Thinking deeply about and clearly articulating the product strategy to stakeholders

Key Responsibilities

• Drive the Ray Data product roadmap - Balance open source Ray Data feature development with RayTurbo Data commercial differentiation to ensure that both Ray Data becomes the open source standard for AI data processing and RayTurbo remains sufficiently compelling.

• Drive open source Ray Data adoption - Focus on community growth, developer experience, and ecosystem integrations

• Market Positioning & Enablement - Work closely with Product Marketing on strategic market positioning, field enablement, and competitive analysis to maintain differentiation.

• Customer engagement - Drive key customer engagements assisting sales and field engineering teams.

Required Qualifications

• 3+ years of product management experience with technical products

• Strong technical background in distributed systems, ML infrastructure, or data processing

• Experience working with developer and enterprise audiences

• Strategic thinking with ability to balance competing priorities and stakeholder needs

• Located in or willing to relocate to the Bay Area

Preferred Qualifications

• Prior experience with open source products and commercial monetization strategies

• Background in ML tooling, data infrastructure, or developer tools

About Ray Data

Ray Data is a scalable data processing library built on Ray Core that provides flexible and performant APIs for distributed data processing. It enables offline batch inference and data preprocessing for ML training, scaling data processing to large clusters while maintaining ease of use for developers.