Box
Technology
MachineLearningEngineerIII,SearchRelevance
Neural analysis suggests this role is
optimal for Senior candidates.
“Machine Learning Engineer III, Search Relevance at Box. Skills: Search relevance, Machine learning, Distributed systems, Information retrieval. Design components for ranking. Design components for retrieval”
What You'll Achieve.
Improve relevance; Improve latency; Serve queries in real time
Industry & Context.
Root cause analysis
On-call rotation
What They're Looking For.
Must Have
3+ years backend systems experience, 3+ years data pipelines experience, Proficient in Java, Scala, C++, Production-grade Python, BS in Computer Science or equivalent
Nice to Have
Experience with Elasticsearch, Experience with Solr, Experience with Lucene, Experience with custom search, Knowledge of relevance tuning, Knowledge of learning-to-rank, Knowledge of offline/online experimentation, Exposure to vector search, Exposure to dense embeddings, Exposure to sparse embeddings, Exposure to hybrid retrieval, Familiarity with IR fundamentals, Familiarity with query understanding, Experience with Kubernetes, Experience with Terraform, Experience with GCP, Experience with AWS, Experience with Azure, Practical exposure to PyTorch, LLM familiarity
What You'll Do.
Design components for ranking
Design components for retrieval
Design components for recommendations
Implement production features
Leverage semantic search
Leverage hybrid search
Leverage LLM-enabled retrieval
Contribute to offline evaluation
Contribute to online evaluation
Contribute to A/B tests
Contribute to relevance tuning
Develop reliable microservices
Develop observable microservices
Develop near real-time indexing pipelines
Own projects from design to rollout
Write operational runbooks
Improve data pipelines
Improve feature pipelines
Contribute to team best practices
Participate in on-call rotation
How You'll Work.
Team & Collaboration
Senior engineers; Product partners; Data partners; Infra partners
Process & Methodology
Design docs
Full Job Description
WHAT IS BOX? Box (NYSE:BOX) is the leader in Intelligent Content Management. Our platform enables organizations to fuel collaboration, manage the entire content lifecycle, secure critical content, and transform business workflows with enterprise AI. We help companies thrive in the new AI-first era of business. Founded in 2005, Box simplifies work for leading global organizations, including JLL, Morgan Stanley, and Nationwide. Box is headquartered in Redwood City, CA, with offices across the United States, Europe, and Asia. By joining Box, you will have the unique opportunity to continue driving our platform forward. Content powers how we work. It’s the billions of files and information flowing across teams, departments, and key business processes every single day: contracts, invoices, employee records, financials, product specs, marketing assets, and more. Our mission is to bring intelligence to the world of content management and empower our customers to completely transform workflows across their organizations. With the combination of AI and enterprise content, the opportunity has never been greater to transform how the world works together and at Box you will be on the front lines of this massive shift. The Search Relevance team at Box powers discovery across billions of files, enabling customers to find the right content quickly, securely, and intelligently. As we expand into a new era of AI-powered content understanding, we’re investing in the foundation that makes great search possible: reliable systems, strong signals, and models that learn from real-world usage. This is a rare opportunity to work at the intersection of information retrieval science, applied machine learning, and large-scale distributed systems. You’ll be building the infrastructure that powers intelligent content discovery for Fortune 500 companies—where milliseconds matter, relevance is measurable, and your experiments directly impact how millions of users work. We’re looking for a Machine
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