Builders' Echo
About
Builders' Echo is a two-sided, skills-based hiring marketplace where companies run real-world challenges based on the actual work for a role and evaluate candidate submissions through blind judging to reduce bias in hiring. Teams can host scoped contests, verify submissions via GitHub OAuth, and use integrated Stripe payments to handle entry fees and prize payouts, creating a fair, scalable way to identify top performers based on demonstrated work rather than resumes. For builders, it's a chance to be seen on merit alone. Browse open contests, submit your work, and compete for real prizes — while getting discovered by companies hiring for roles you'd actually want. No cover letters, no keyword screens, no interview nerves. Just your output speaking for itself. Whether you're a new grad trying to break in, a self-taught developer without a big-name pedigree, or an experienced engineer tired of jumping through hoops — Builders' Echo levels the playing field. Your GitHub history, your shipped features, and your problem-solving approach matter more than where you went to school or how you perform under pressure in a 45-minute whiteboard session. We're building the hiring process we wish existed: one where the work does the talking, the best submission wins, and both sides walk away with something real.
Open contests
4Document Information Extraction Pipeline with LLM Prompting and Evaluation
Overview Scotiabank's Global AI & ML team processes thousands of complex financial documents (loan applications, contracts, financial statements) daily. Building a rel...
Production-Ready Multi-Task Ranking API for E-commerce Search & Recommendations
Overview Instacart's ranking platform must jointly optimize for relevance, conversion, and long-term value rather than any single metric. In this challenge you'll buil...
Click-Through Rate Prediction for Programmatic Ad Auctions
Overview StackAdapt's bidder must estimate click-through rates (CTR) in milliseconds to decide whether to bid on an ad impression and at what price. Accurate, well-cal...
Reddit-Style Feed Ranking: Feature Engineering, Multi-Model Comparison, and Dockerized FastAPI Serving Endpoint
Overview You will design and implement a production-oriented ML ranking pipeline for a Reddit-style feed. Using the fixed-seed synthetic dataset generated by the scrip...
Past contests
3Learning-to-Rank Feed Ranker: Feature Engineering & Gradient Boosted Model on MIND News Dataset
Overview Quora's distribution team connects 300M+ monthly users with content they care about through feed ranking, notifications, and digest emails. A core part of thi...
Build a Two-Tower Retrieval Model for Subreddit Recommendations
Overview Reddit's Feed Relevance team needs to surface relevant subreddits to new or low-activity users who haven't established strong preference signals. A two-tower...
Full-stack feature sprint
Deliver a complete vertical slice of a feature (UI + API + persistence) from our brief. Include a README with architecture decisions, setup instructions, and known tra...