Backend Engineer - Recommendation (all genders)
Core
Build and serve a high-throughput recommendation engine for an e-commerce fashion platform, integrating offline ML models and GenAI features to personalize product and outfit recommendations.
Role type
Senior Backend Engineer specializing in Recommendation Systems and GenAI integration
Builds
Real-time recommendation engine, GenAI fashion advisor, reverse-ETL pipelines, and personalization logic for product pages
Domain
E-commerce / Fashion / Machine Learning / GenAI
Deliverable
production ML models | product features | infrastructure
Required skills
Node.js/TypeScript, Redis/Valkey data modeling, high-throughput API design, ML model serving, reverse-ETL pipeline management, A/B experimentation, low-latency system design
Preferred skills
Matrix factorization, image embeddings, streaming GenAI/LLM product experience, AWS serverless (DynamoDB, SQS), OpenSearch k-NN, performance profiling (clinic.js, flamegraphs), load testing (k6)
Technologies
Node.js, TypeScript, Valkey, DynamoDB, OpenSearch, BigQuery, SQS, Gemini, Protobuf, Avro, k6, clinic.js
Responsibilities
Develop recommendation engine logic including feed assembly, fallback chains, and diversity algorithms; Serve offline-trained ML models at scale; Build GenAI features like streaming fashion advisors; Own reverse-ETL pipelines moving model outputs to hot stores; Instrument coverage and track business metrics; Shape architecture alongside Tech Lead
Seniority
Senior, hands-on IC