Joblaze summary

In the role of Product Manager for Interface Design at Hippocratic AI, the individual will focus on enhancing the user experience of a labeling and annotation tool, ensuring it is efficient and engaging for the internal team. Key skills include expertise in consumer product design, gamification principles, and the ability to define and track interface metrics. This position is ideal for someone with a background in product management and a strong understanding of user interaction, particularly in high-volume task environments. The role emphasizes collaboration with technical product managers and engineering to implement meaningful interface changes.

Joblaze insights

Listed 4 days ago — first seen on Joblaze October 29, 2026. Last confirmed on Hippocratic AI's careers page November 2, 2026.
Gamification appears in 0.6% of 155 comparable mid product roles in United States.

Quick facts

Is the Product Manager, Labeling & Annotation Experience role remote?: No — this is an on-site role in Menlo Park, CA.
Where is the role based?: Hippocratic AI is hiring for this position in Menlo Park, CA.
What's the tech stack?: Joblaze extracted these technologies from the posting: Gamification, UX, interface design.
What seniority level is this role?: Hippocratic AI targets mid-level candidates for this position.
Is this full-time or contract?: Full-time for this Product Manager, Labeling & Annotation Experience role at Hippocratic AI.

From the original posting

About the Role

This role owns the UX of a tool, not a feature — the labeling and annotation interface that HAI's internal annotation team lives in every day. As Product Manager, Interface Design, you're a UX/interface expert who applies consumer-product and gamification thinking to a workflow most companies treat as pure ops tooling, optimizing it for efficiency, accuracy, and engagement. You'll work closely with the Technical Product Managers who run labeling operations day to day, plus Engineering to ship interface changes.

What You'll Do

Design for efficiency and accuracy

Redesign labeling workflows and interaction patterns that measurably cut the time and error rate per labeling task.
Decide which interface changes ship first, prioritizing around where labelers actually lose time or make mistakes today, not a generic backlog.
Define the interface-level metrics (task completion time, error/rework rate) that prove a design change worked.

Design for engagement

Apply gamification and behavioral-psychology principles to keep labelers accurate and engaged across long task queues, not just fast.
Own the reward, progress, and feedback mechanics inside the labeling app, deciding what actually motivates sustained quality rather than just throughput.

Partner across the annotation org

Work directly with the Technical Product Managers running labeling projects to translate what's slowing labelers down into interface changes, rather than working from secondhand requirements.
Partner with Engineering to ship interface and workflow changes, making the sequencing calls when priorities compete.

Location and Travel

We believe the best ideas happen together. To support fast collaboration and a strong team culture, this role is expected to be in our Menlo Park office five days a week.

What You Bring

Must-Have

5 years of consumer app or web product experience with direct ownership of interface/interaction design decisions — not just requirements writing
Experience applying gamification or behavioral-psychology principles to product design
Comfort defining and tracking interface-level metrics (engagement, accuracy, completion time) and iterating against them
BA or BS is Required

Nice-to-Have

Experience designing or improving a labeling/annotation interface specifically, or a similarly repetitive, high-volume task tool
Background at a data-labeling, crowdsourcing, or annotation platform
Familiarity with the operational side of managing labeling task queues

What Success Looks Like

Within a year, the labeling interface shows measurably higher labeler engagement and annotation accuracy than today's baseline, with the improvement clearly attributable to this person's design decisions rather than incidental changes elsewhere in the pipeline.

Standard company text repeated across Hippocratic AI's postings is omitted here.

Product Manager, Labeling & Annotation Experience