Who is our client?

Our client is a large-scale technology organization with a strong focus on engineering, data, and AI. They are continuing to invest in AI/ML platform capabilities that enable teams to build, operate, and scale machine learning and intelligent applications more effectively.

About the Role

This role is for a highly technical Product Manager who will lead machine learning/LLM platform initiatives. You will work at the intersection of product, platform engineering, data, and AI to improve tooling, automate workflows, and strengthen the reliability and scalability of technical platforms.
*Relocation sponsorship provided

Responsibilities

• Own and drive the roadmap for machine learning/LLM platform capabilities.
• Identify platform gaps, workflow inefficiencies, and opportunities to improve automation, reliability, and scale.
• Work closely with software, data, and ML engineers to define requirements and deliver platform improvements.
• Build product direction for internal tooling, self-service dashboards, workflow automation, and platform enablement.
• Support platform capabilities across data integration, model operations, deployment, observability, and monitoring.
• Work with engineering on architectural direction, scalability decisions, and execution trade-offs.
• Define success metrics and measure adoption, performance, and impact of platform initiatives.
• Drive cross-functional alignment and communicate effectively with both technical and non-technical stakeholders.
• Lead the change management and help users successfully adopt new platform capabilities.
• Translate complex technical needs into clear product priorities and execution plans.

Qualifications

• 5-7 years of experience as a Product Manager or in a highly technical product role.
• Prior hands-on experience in software engineering, machine learning engineering, or data engineering is required.
• Strong understanding of platform products, technical systems, and engineering workflows.
• Strong knowledge of MLOps, including monitoring, evaluation, deployment, versioning, observability, and model lifecycle management.
• Experience working closely with engineers on roadmap, architecture, and delivery.
• Strong analytical and problem-solving skills.
• Ability to communicate technical concepts clearly to a wide range of stakeholders.
• Comfortable working in fast-paced, high-scale, and ambiguous environments.
• Strong ownership mindset and the ability to lead complex technical initiatives end-to-end.