10 дней назад
Backend Engineer - Recommendation (all genders)
60 000 - 70 000€
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Backend Engineer - Recommendation (all genders) (Node.js/TypeScript, ML): Developing the recommendation engine for personalized e-commerce pages with an accent on high-throughput serving, model integration, and real-time personalization. Focus on designing low-latency recommendation APIs, operating 10k+ RPS systems, building reverse-ETL pipelines, and delivering streaming GenAI features with controlled token costs.
Location: Hamburg or Berlin, Germany
Salary: EUR 60,000–70,000 yearly
Company
is a European e-commerce company combining fashion and technology to create personalized online shopping experiences.
What you will do
- Develop the recommendation engine for the homepage, product pages, and outfit pages using Node.js and TypeScript.
- Serve offline-trained machine learning models, including matrix factorization, brand similarity, and image embeddings, at Black Friday scale.
- Design personalization logic covering feed assembly, fallback chains, deduplication, diversity, and A/B experimentation.
- Build streaming GenAI product features, including a Gemini fashion advisor, with low latency, session state, and token cost control.
- Own reverse-ETL pipelines that move BigQuery model outputs into high-performance data stores.
- Monitor recommendation coverage, track business metrics, and shape the architecture with the Tech Lead.
Requirements
- 3+ years of experience building high-throughput backend services.
- Strong Node.js and TypeScript experience, or the ability to transition quickly from Java, Go, or Kotlin.
- Deep experience with Redis or Valkey data modeling, caching hierarchies, TTLs, invalidation, and binary payloads such as Protobuf or Avro.
- Experience operating APIs at 10k+ requests per second under strict latency SLOs.
- Ability to integrate model scores, embeddings, or LLM features into live backend systems.
- Clear communication skills in English and availability to work in Hamburg or Berlin, Germany.
Nice to have
- Recommendation systems fundamentals, including collaborative filtering, matrix factorization, cold-start handling, and diversity algorithms.
- Streaming GenAI or LLM product experience, including chat UX, prompt caching, or guardrails.
- AWS serverless experience with DynamoDB, SQS/SNS, and OpenSearch k-NN indices.
- Performance profiling and load testing with tools such as clinic.js, flamegraphs, or k6.
Culture & Benefits
- Flat hierarchies, direct communication, pragmatic decisions, and clear ownership.
- Inclusive environment focused on acceptance, inclusion, and diverse perspectives.
- Team lunches, afterwork drinks, company events, and informal opportunities to connect.
- Additional employee benefits are provided through the company benefits program.
Hiring process
- Apply online through the career page.
- The hiring team will follow up after reviewing the application.
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