Machine Learning Engineer III, Search Relevance

About this role

Box seeks a Machine Learning Engineer III to build and optimize search relevance systems powering intelligent content discovery across billions of files. You'll design ranking and retrieval components, implement modern retrieval techniques, and own projects from design through production deployment in a fast-paced, metrics-driven environment.

What you'll do

• Design and build ranking, retrieval, and recommendation components to improve relevance and latency
• Implement production features using embeddings, semantic search, and LLM-enabled retrieval
• Conduct offline/online evaluation, A/B testing, and relevance tuning using IR metrics
• Develop reliable microservices and near real-time indexing pipelines for distributed systems
• Own well-scoped projects end-to-end with design documentation and operational runbooks
• Participate in on-call rotation and support production incident response

What they're looking for

• Backend or distributed systems development (3+ years)
• Java, Scala, C++, or Python (production-grade preferred)
• Search, ranking, recommendations, or applied ML in production
• Data pipelines and streaming systems (Kafka, Pub/Sub)
• Cloud-native microservices, CI/CD, and observability
• Information retrieval fundamentals and learning-to-rank concepts
• Vector search and hybrid retrieval architectures
• Elasticsearch, Solr, or custom search systems