Glean
Machine Learning Engineer, Search Quality
About this role
Glean seeks a Machine Learning Engineer to enhance search quality and AI capabilities across their enterprise Work AI platform. You'll develop ranking signals, train personalization models, adapt language models to customer data, and integrate LLMs with search to deliver intelligent, context-aware responses at scale.
What you'll do
- Design and implement new signals to improve search personalization and ranking
- Train models to capture signal interactions in the ranking system
- Develop domain-adaptation techniques for language models on customer corpora
- Explore novel approaches combining LLMs with search engines for complex question-answering
- Write production-ready, maintainable, and well-tested code
- Mentor junior engineers and collaborate across cross-functional teams
What they're looking for
- Machine learning framework proficiency (PyTorch, TensorFlow, etc.)
- Python, Go, Java, or C++
- Search, recommendation systems, or NLP experience
- Data analysis and statistical reasoning
- Model design, training, and production deployment
- Large-scale systems and distributed computing
- SQL or data querying
- Git and version control
Benefits
- Medical, Vision, and Dental coverage
- Generous time-off policy
- 401k plan with company contribution
- Home office improvement stipend
- Annual education and wellness stipends
- Daily healthy lunches and company events
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Glean
Glean builds a Work AI platform that helps enterprises access and leverage their internal data intelligently. The company is hiring backend engineers, infrastructure specialists, fullstack engineers, and billing platform leads to develop scalable features, robust data infrastructure, consumption-based billing systems, and enterprise-grade storage and analytics capabilities.
- Website
- glean.com
Likely interview questions
- Describe a time you designed and shipped a production ML model—what were the key challenges and how did you validate its quality?
- Walk us through how you would approach training a ranking model to capture interactions between multiple signals in a search system.