Lead machine learning platform initiatives, own and drive roadmap, and work closely with engineers to define requirements and deliver platform improvements.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Job Description
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
- 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.
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- 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.
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