Senior/Staff Applied Scientist
Mountain View · Mountain View, CA (HQ) · San Francisco · USD 180,000-330,000 / year · 5+ years experience · Hybrid · Posted Oct 5, 2026
At a glance
- Experience
- 5+ years experience
- Workplace
- Hybrid
- Location
- Mountain View · Mountain View, CA (HQ) · San Francisco
- Salary
- USD 180,000-330,000 / year · Base salary
About Glean
- Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles.
- At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level.
- Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality.
- If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more - deeply embedded where people get things done. You’ll ship agentic capabilities on an open, extensible stack, with the craft and care required for enterprise trust, as we bring Work AI to every employee, in every company.
About the role
- Glean is building a world-class Data Organization and is seeking a Senior/Staff Applied Scientist for its San Francisco office.
- This role focuses on developing A/B experimentation platforms, conducting end-to-end evaluations for hero use cases, and establishing best practices across evaluation problems.
Responsibilities
- Collaborate with product data science and engineering teams to identify techniques, tooling, and process improvements in online A/B experimentation to assist rigorous decision making across all relevant product domains.
- Develop and maintain our A/B experimentation platform based on stakeholder feedback.
- Write code or identify vendors to deploy these techniques to production in a scalable manner that's easy to use by engineering, product data science, product management, and design teams.
- Conduct end-to-end evaluation of various hero use cases like document/URL uploads, including evaluation set generation, coming up with evaluation criteria, and methods to interpret the results.
- Break down end-to-end evaluations into more granular evaluation of various tasks & skills including but not limited to content summarization/analysis/generation, multi-step reasoning & strategizing, tool selection & use, coding & system design.
- Design, develop, and own best practices, tools, and processes across various evaluation problems, e.g., query intent classification, standardizing the use of best statistical principles to handle LLM stochasticity, and industry benchmarking.
Requirements
- 5+ years of experience as a Master's degree holder, or 3+ as a PhD degree holder (Master's/PhD degree in Statistics, Mathematics, Computer Science, or another quantitative field).
- Strong in statistics and/or machine learning, with experience applying these skills into tangible improvements in products, internal tools, and processes in a pragmatic way that puts business urgencies first.
- Very proficient in Python, proficient enough to maintain an internal source-controlled library used by dozens of others.
- Concise and precise in written and verbal communication, where technical documentation is a strong suit.
- Proficient in SQL and the modern data stack (e.g., source-controlled dbt pipelines for ETL/ELT).
- Strong at defining good product KPIs/guardrail metrics, dashboarding, and analysis of raw data to derive strategic insights.
- Experience in B2B SaaS.
- Experience working on ranking, developing, and maintaining A/B experimentation platforms and/or ML measurement problems.
- Passionate about using AI to improve the productivity of data teams as well as non-data professionals trying to derive more value of their company's data.
Benefits
- Medical, Vision, and Dental coverage
- Generous time-off policy
- 401k plan contribution opportunity
- Home office improvement stipend
- Annual education and wellness stipends
- Regular events and vibrant company culture
- Healthy lunches daily
Workplace
- This role is hybrid (4 days a week in the San Francisco office).
Skills
- Python
- SQL
- Dbt
- Machine Learning
- Statistics
