Senior/Staff Applied Scientist
Mountain View San Francisco Senior AI Research
At a glance
Senior AI Research role at Glean. Mountain View · $180,000–$330,000 base.
SalaryStated by Glean
$180,000 – $330,000
Base salary for this role, in USD per year, as published in the posting.
This role, from GleanOur estimate for the market: $238,000–$268,583Median $248,750
The range includes the market median of $248,750 for senior AI research roles in Mountain View.
Worked out from 10 postings that stated pay, median $248,750. Last updated Oct 5, 2026.
RoleAI Research
SenioritySenior
LocationMountain View
Base pay$180,000–$330,000
PostedOct 5, 2026 · 2w ago
Also hiring inSan Francisco
Role brief
aimlroles summary, based on the employer's posting.
What you'll do
- Improve online A/B testing methods and workflows with product science and engineering teams
- Build and maintain the experimentation platform, using stakeholder input to guide its development
- Evaluate key use cases such as document and URL uploads, from building test sets to interpreting results
- Break broad evaluations into checks for summarization, reasoning, tool use, coding and other capabilities
- Create evaluation standards and tools for query intent, LLM variability and industry comparisons
What you bring
- A master’s in a quantitative field plus at least five years of experience, or a PhD and at least three years
- Strong statistics or machine learning skills, applied to practical product, tool or process improvements
- Advanced Python skills, with the ability to maintain a shared, source-controlled library
- Experience with B2B SaaS and A/B testing platforms or machine-learning measurement
Who this fits
This role suits a senior applied scientist who can combine statistical rigor with practical product evaluation and clear technical documentation. You’ll work four days a week from the Mountain View or San Francisco office.
From the employer
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. You'll be 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 composed of product data science, applied science, data engineering and business intelligence groups.
You will:
By clicking “Submit Application,” I confirm that I have read the Global Data Privacy Notice and the Applicant Arbitration Agreement, and I agree to the terms.
- 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, industry benchmarking.
- You have 5+ years of experience as a Masters degree holder, 3+ as a PhD degree holders (Masters/PhD degree in Statistics, Mathematics or Computer Science, or another quantitative field)
- You’re strong in statistics and/or machine learning. You have experience in applying these skills into tangible improvements in products, internal tools, and processes in a pragmatic way that puts business urgencies first.
- You are very proficient in Python, e.g. proficient enough to maintain an internal source-controlled library used by dozens of others.
- You are concise and precise in written and verbal communication. Technical documentation is your strong suit.
- You are proficient in SQL and the modern data stack (e.g. source-controlled dbt pipelines for ETL/ELT).
- You are strong at defining good product KPIs/guardrail metrics, dashboarding and analysis of raw data to derive strategic insights.
- You have experience in B2B SaaS.
- You have experience working on ranking, developing, and maintaining A/B experimentation platforms and/or ML measurement problems.
- You are 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.
- This role is hybrid (4 days a week in our Mountain View or San Francisco office)
By clicking “Submit Application,” I confirm that I have read the Global Data Privacy Notice and the Applicant Arbitration Agreement, and I agree to the terms.