Machine Learning Engineer, Enterprise Brain

Glean Work is hiring a Machine Learning Engineer, Enterprise Brain in Mountain View, United States. It pays $200k-$280k a year and Level rates it ; you can apply on Level.

Level's read on this job

Builds AI ●●●● is how Level rates this machine learning engineer role: the job is building AI systems.
Pay on this posting starts in line with the typical machine learning engineer posting on Level.
Some of the work can be done remotely, according to the posting.
The posting mentions PyTorch, TensorFlow and AI agents among its tools and skills.
Glean Work has 135 other open roles on Level.

AI in this role

Build proactive AI products and machine learning capabilities for Glean's Enterprise Brain team.

pytorchtensorflow

ai-agentsfine-tuningmachine-learningartificial-intelligenceenterprise-searchsoftware-engineering

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 seeking a few Machine Learning engineers who want to focus on a combination of Quality and traditional ML work to help us build the Enterprise Brain. The Enterprise Brain team is developing a suite of proactive AI products that aims to revolutionize enterprise workflows by proactively detecting and automating tasks for users - thus unlocking true productivity. This is built on top of a deep user understanding and state of the art Enterprise graph. The project involves using both LLM and other advanced ML techniques, agent orchestration and cutting-edge ranking techniques.

You will:

Work on deeply challenging ML problems involving user understanding and task prediction.
Invent new LLM workflows and signals to improve reasoning, planning, and personalization.
Design and optimize reinforcement learning and fine-tuning approaches to improve the quality of understanding, prediction and other agentic systems.
Lead development of scalable evaluation, benchmarking, and optimization loops.
Build and maintain robust ML pipelines for enterprise and knowledge graph construction.
Drive initiatives to measure, monitor, and improve data quality, model quality, and end-to-end system performance.
Collaborate with cross-functional teams to deeply understand customer pain points and deliver high-quality, production-ready ML solutions.
Mentor junior engineers or learn from experienced ones in a tight-knit, high-velocity environment.

About you:

You bring 6+ years of industry experience in machine learning engineering.
You hold a BA/BS in computer science, math, sciences, or a related field.
You have a proven ability to design, build, and ship production-ready models and systems.
You bring demonstrated expertise in ML evaluation, benchmarking, and data quality.
You are proficient in an ML framework of your choice, such as TensorFlow or PyTorch.
You thrive in a fast-moving, ambiguous environment, turning open-ended customer and ML problems into clear priorities and production-ready solutions.
You balance speed with quality, making pragmatic tradeoffs to deliver measurable progress without losing sight of production readiness.

Location:

This role is hybrid (4 days a week in our Mountain View office)

Compensation & Benefits: The standard base salary range for this position is $200,000 - $280,000 annually. Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for variable compensation, equity, and benefits. We offer a comprehensive benefits package including competitive compensation, Medical, Vision, and Dental coverage, generous time-off policy, and the opportunity to contribute to your 401k plan to support your long-term goals. When you join, you'll receive a home office improvement stipend, as well as an annual education and wellness stipends to support your growth and wellbeing. We foster a vibrant company culture through regular events, and provide healthy lunches daily to keep you fueled and focused. We’re committed to building and sustaining a diverse, inclusive workplace. We strive to attract and retain people with a wide range of backgrounds, experiences, and perspectives, and we do not discriminate on the basis of gender, ethnicity, sexual orientation, religion, civil or family status, age, disability, or race. #LI-HYBRID AI-First Mindset at Glean: At Glean, AI fluency is core to how we work and we're committed to ensuring every new hire feels confident integrating AI into their everyday work. As part of the interview process, you'll complete a brief AI-focused exercise or discussion so we can understand how you think about, design, and use AI to drive impact in your role. Feel free to reference any tools, platforms, or workflows you use today — prior Glean experience isn't required. Global Data Privacy Notice for Job Candidates and Applicants: Depending on your location, the General Data Protection Regulation (GDPR), California Consumer Privacy Act (CCPA), or other privacy laws may regulate the way we manage the data of job applicants. Our full notice outlining how data will be processed as part of the application procedure for applicable locations is available in our Privacy Policy. By submitting your application, you are agreeing to our use and processing of your data as required. US applicants and their applications are subject to arbitration of disputes as outlined in our Applicant Arbitration Agreement.
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.

How we rate this

Machine Learning Engineer, Enterprise Brain at Glean Work rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Key facts

Machine Learning Engineer, Enterprise Brain is an open job at Glean Work.
Level rates this role AI Level 4 of 4: Builds AI.
The listed salary is $200k-$280k a year.
The role is based in Mountain View, CA and is marked remote.
The job was posted on October 16, 2026.
Seniority: mid.
Applications are handled by Glean Work. Apply on Glean Work

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

AI agentsFine-tuningMachine learningArtificial IntelligenceEnterprise SearchSoftware EngineeringPyTorchTensorFlow

Also common in machine learning engineer jobs at this level

Python Deep learning AWS Generative AI C++Spark

Pay

This job starts at: $200k
Typical machine learning engineer job: $197k

This posting starts close to the typical machine learning engineer job. See machine learning engineer jobs

Questions you could be asked

How do you decide when an AI agent can act on its own versus asking for approval first?
Walk me through fine-tuning a model: what data did you use, and how did you check the result?
Tell me about a project where machine learning was part of your work. What did you do?
Tell me about a project where artificial intelligence was part of your work. What did you do?
Tell me about a project where enterprise search was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: AI agents, Fine-tuning, Machine learning, Artificial Intelligence, and Enterprise Search. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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