Senior Staff Software Engineer (Search & Recommendation)

Описание

Cantina is an AI-startup that creates AI characters and builds a platform for human interaction. This role involves owning the end-to-end architecture and roadmap for search and recommendations, including retrieval, ranking, and relevance quality.

Responsibilities

• Own the architecture and roadmap for search and recommendations end to end — query understanding, retrieval, ranking, and the surfaces they feed: search, discovery, the home feed, and our trending and creator leaderboards.
• Make relevance a measured discipline rather than an opinion: define the quality metrics per surface, build the offline evaluation and golden-set tooling, and run the online experiments that decide whether a ranking change ships.
• Design and evolve the ranking stack — engagement signal pipelines, decay and freshness models, and the pattern we use to combine pre-computed index-time signals with live re-ranking at query time.
• Own OpenSearch in production: index and mapping design, reindex and cutover safety, query performance, cost, and the operational headroom of the clusters behind every discovery surface.
• Build candidate generation and personalization for recommendation surfaces, and partner with data and ML on the feature pipelines and models behind them.
• Work directly with Product and Trust & Safety on what “good” means for each surface — quality gates, cold-start behavior for brand-new creators and characters, and what must never be recommended.
• Set the engineering standard for the area: instrumentation, flag-gated rollouts, and runbooks that let other teams change ranking behavior without breaking it.
• Act as the technical point of contact for discovery across backend teams, and mentor the engineers whose work touches it.

Requirements

• 10+ years building production software, with substantial depth in search, ranking, recommendations, or ML-driven relevance on a consumer-scale product.
• Hands-on expertise with a production search engine — OpenSearch, Elasticsearch, Lucene, Vespa, or similar — covering index and analyzer design, relevance tuning, and operating the cluster, not only querying it.
• A rigorous approach to relevance measurement: you have owned offline evaluation, golden sets, and A/B or interleaving frameworks, and you can explain what moved a metric and why.
• Fluency across the recommender stack — candidate generation, feature pipelines, embedding retrieval, re-ranking — and a working understanding of the serving constraints that make an offline win fail online.
• Strong distributed systems and backend fundamentals, with production experience in Go or a comparable systems language, and comfort in the data layer behind it (SQL warehouses, streaming and batch pipelines).
• Demonstrated ownership of an ambiguous area: you have picked up something with no dedicated owner, decided what mattered, and can show the result.
• Clear written communication and the judgment to work with Product on real tradeoffs between relevance, freshness, safety, and latency.

Nice to have

• Experience with AI-generated or rapidly growing content catalogs, severe cold-start conditions, or ranking under trust-and-safety constraints.

We offer

• Anticipated annual base salary range: $250,000 - $320,000 (USD).
• Competitive salary and generous company equity.
• Medical, dental, and vision insurance – 99.99% of premiums covered by Cantina.
• 42 days of paid time off, including: 15 PTO days, 10 sick days, 15 company holidays, 2 floating holidays.
• Generous parental leave & fertility support.
• 401(k) retirement savings plan.
• Lifestyle spending account – $500/month to use however you’d like.
• Complimentary lunch and snacks for in-office employees.
• One Medical membership, and more!