Principal Product Manager, Machine Learning Platform
Listed on 2025-12-23
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IT/Tech
AI Engineer, Cloud Computing, Systems Engineer, Product Designer
Job Title
Principal Product Manager, Machine Learning Platform
Job DescriptionAbout The Position | Major goals and objectives and location requirements
We’re seeking a Principal Platform Product Manager to drive the evolution of our internal platforms that power content discovery and publishing experiences across People Inc.’s 30+ brands, reaching over 100M users monthly. This role sits at the intersection of engineering excellence and product strategy—focused on building scalable, reusable ML-enabling services that accelerate development velocity, reduce duplication, and improve consistency across teams.
As a senior IC partner to engineering and data science leadership, you’ll define and champion the roadmap for foundational capabilities such as search, recommendations, vector-based retrieval, and LLM enablement. You’ll ensure these platform services are robust, performant, well-documented, and widely adopted. Success requires balancing thoughtful product curation, long-term architectural coherence, and tactical developer needs.
This role reports to the VP of Product, Core Platform, and collaborates closely with Data Services and Platform Engineering leadership to ensure we’re solving the right problems with the right strategic focus.
Hybrid 3x a week- (New York, NY)
In-office Expectations:
This position is hybrid in-office, with the ability to work remotely for up to 2 days per week.
- Define and maintain a platform roadmap aligned with company-wide goals and engineering priorities.
- Prioritize investments that reduce redundant work, improve developer satisfaction, and unlock new end-user capabilities.
- Make deliberate tradeoffs—focusing as much on what not to build as what to include to preserve platform coherence.
- Act now not later, move with urgency while staying aligned to the long-term vision.
- Champion the platform as a product, not just a set of tools—requiring careful, opinionated curation.
- Avoid the “feature shop trap” by recognizing patterns in requests and designing extensible, self-service capabilities.
- Promote modularity, standardization, and reusability across services to reduce fragmentation and technical debt.
- Deliver with intention, by thoughtfully balancing user problems with platform coherence.
- Lead multi-team initiatives for search, recommendations, content enrichment, and LLM infrastructure.
- Serve as the connective tissue between platform engineering, infrastructure, data science, and consuming teams.
- Collaborate respectfully to align stakeholders around shared technical outcomes.
- Treat internal developers as primary customers—improving API usability, documentation, and onboarding.
- Build trusted, self-serve services with intuitive interfaces and strong feedback loops.
- Make it matter by solving real developer pain points with empathy and insight.
- Experience designing compelling migration paths and driving adoption of new platform capabilities.
- Ability to incentivize teams to adopt platform services through demonstrable value through efficiency, reliability, or new functionality.
- Support teams throughout the transition process to reduce total cost of ownership.
- Champion accountability in getting teams successfully onto future-proof platforms.
- Partner with engineering to ensure platform reliability, stability, and performance.
- Champion SLOs, observability, and self-healing capabilities as foundational product attributes.
- Avoid operational burden falling to users by proactively addressing edge cases and failure modes.
- Expect integrity in how we build, test and scale platform services.
- Define and track platform leverage metrics—e.g., engineering hours saved, duplicated work eliminated, system uptime.
- Balance platform health metrics with adoption, developer satisfaction, and impact to end-user outcomes.
- Build feedback loops to continuously iterate on platform capabilities.
- Identify and prioritize future-facing…
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