Shipd is our gamified data collection platform that transforms boring annotation into an addictive, competitive experience. 16,000+ contributors have signed up organically because “nerds want to get paid to code.” With quest-based campaigns, bounty rewards, streaks, and community features, Shipd aims to attracts the best talent for complex data production. Now we’re looking for a Product Engineer to help us scale the platform into the “Duolingo for coding bounties” or “Kaggle but paid”
Build the Quest Builder system: Create reusable components, UI generators, and multi-step pipelines that shrink quest setup from a week to a day.
Own developer experience tooling: Extend our VS Code fork, browser extension (Moody Blues), and trace viewer to capture long-form coding workflows with full observability.
Scale the data flywheel: Design features that make the platform engaging enough to bring friends, raise quality through competition, and support any data format without starting from scratch.
Engineer quality at scale: Improve our three-tier eval system (automation, judge models, human review), build real-time feedback, and empower top contributors to become reviewers.
Ship addictive experiences: Blend game mechanics, developer tools, and marketplace dynamics into products that make hours-long data tasks feel rewarding.
Strong product engineering experience—you can own features end-to-end across frontend, backend, and data.
A knack for building systems that scale—infrastructure, pipelines, and abstractions that work across many use cases.
Experience with developer tools (e.g., IDEs, extensions, SDKs, CLIs) or platforms with heavy telemetry/observability.
Curiosity about game design, marketplaces, or community products—how to keep people motivated and engaged.
Excellent communication and product sense—you can frame trade-offs clearly and design with both users and internal teams in mind.
Comfort with ambiguity—happy to prototype, iterate fast, and pivot based on feedback.
Builder’s mindset: scrappy, resourceful, motivated by hard problems.
Excited by human-AI collaboration and how product design shapes outcomes.
Pride in craft: you care about both quality and speed.
Desire to help define the “experience foundations” for frontier data collection.
Experience in AI/ML, crowdsourcing platforms, or online education/gamification.
Familiarity with marketplace dynamics or contributor ecosystems.
Background in scaling evaluation or quality systems for complex work.
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