Machine Learning Engineer, Search Quality
Mountain View Mid-level Machine Learning Engineering
At a glance
Mid-level Machine Learning Engineering role at Glean. Mountain View · $140,000–$265,000 base.
SalaryStated by Glean
$140,000 – $265,000
Base salary for this role, in USD per year, as published in the posting.
This role, from GleanOur estimate for the market: $188,900–$241,250Median $213,750
The range includes the market median of $213,750 for mid-level machine learning engineering roles in Mountain View.
Worked out from 12 postings that stated pay, median $213,750. Last updated Oct 17, 2026.
RoleMachine Learning Engineering
SeniorityMid-level
LocationMountain View
Base pay$140,000–$265,000
PostedApr 8, 2022 · 4y ago
Role brief
aimlroles summary, based on the employer's posting.
What you'll do
- Create fresh signals that make search results more personal, then train ranking models to learn how those signals interact
- Adapt language models to each customer’s content and find ways to combine LLMs with search for complex questions
- Build production code that is readable, maintainable and testable
- Work with customers to understand their problems and apply the tools needed to solve them
- Support junior engineers through mentoring and learn from experienced teammates
What you bring
- At least two years of experience and a bachelor’s degree in computer science, math, science or a related area
- Experience with machine learning systems such as search, recommendations or natural language processing
- A record of designing, building and launching production models, plus strong data analysis skills
- Fluency in an ML framework and strong coding ability in a language such as Python, Go or Java
Who this fits
This role suits a mid-level engineer who enjoys applied ML, customer problem-solving and close collaboration across teams. You’ll mentor less experienced engineers or learn from senior colleagues. The role is hybrid, with four days each week in the Mountain View or San Francisco office. The stated base salary range is $140,000 to $265,000 per year.
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 looking for engineers to help build the world’s best search and assistant product for work. Our engineers work on a range of systems across the stack, including query understanding, document understanding, domain-adapted language models, natural language question-answering, evaluation, and experimentation. We interact regularly with customers, deeply understand their pain points, and use whatever tool is necessary, simple or complex, to solve their problems.
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.
- Invent new signals to improve the personalization of our search engine
- Train a model to capture interactions between signals in our ranking system
- Design smarter ways to domain-adapt language models to each customer’s corpus
- Discover new ways of combining LLMs with search engines to answer complex questions
- Write robust code that’s easy to read, maintain, and test
- Mentor more junior engineers, or learn from battle-tested ones
- 2+ years of experience
- BA/BS in computer science, math, sciences, or a related degree
- Experience working with search, recommendation, natural language processing, or other large systems involving machine learning
- Strong analytical skills and ability to work with data
- Proven ability to design, build, and ship production-ready models
- Proficiency in your ML framework of choice
- Strong coding skills (Python, Go, Java, C++, ...)
- Thrive in a customer-focused, tight-knit and cross-functional environment - being a team player and willing to take on whatever is most impactful for the company is a must
- A proactive and positive attitude to lead, learn, troubleshoot and take ownership of both small tasks and large features
- This role is hybrid (4 days a week in our Mountain View or San Francisco offices)
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.