What you'll be doing:

📍Design, build, and iterate AI and ML-powered ranking and relevance systems (including candidate generation, filtering, personalization, bandits, and learning-to-rank) that balance engagement, quality, and safety while meeting latency and reliability SLOs. 📍Develop features and embeddings for users, content, graph, temporal, and safety signals; establish feature contracts, offline backfills, and online freshness. 📍Stand up vector retrieval and RAG pipelines for semantic search, content understanding, and safety heuristics; tune retrieval quality, token/latency budgets, and evaluation. 📍Build and operate online inference and batch scoring services for LLMs and ML models; optimize throughput, cost, caching, and autoscaling; introduce GPU-aware scheduling where appropriate. 📍Partner with Data Platform on data movement and pipelines (batch and streaming) that power ranking models and analytics; ensure data quality, lineage, documentation, and observability. 📍Partner with Data Science to frame metrics and hypotheses, design trustworthy experiments, analyze results, and productionize improvements. 📍Productionize models end-to-end (training, evaluation, versioning, registries, rollouts, shadowing/canary, rollback) with strong CI/CD and infra-as-code practices. 📍Establish ML observability (data/feature drift, model performance, safety thresholds, online/offline eval, dashboards and alerting) to maintain quality over time. 📍Collaborate cross-functionally with product, design, platform/infra, safety, and CX to align on goals, roadmap, and risk management. 📍Contribute to engineering excellence through documentation, code reviews, reliability improvements, and mentorship to junior engineers.

What we look for in you:

📍3+ years of ML engineering or recommender-systems experience (or equivalent), including shipping production models and improving them iteratively. 📍Strong software engineering fundamentals with proficiency in Python and SQL; experience building reliable services and data pipelines at scale. 📍LLM and AI inference experience, including prompt/program design, evaluation frameworks, agentic workflows, or online performance optimization.

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