Machine Learning Engineer, Enterprise Brain

Glean•Palo Alto, CA

3h•Hybrid

About The Position

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. 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.

Requirements

3+ years of industry experience in AI or Machine Learning Engineering.
BA/BS in computer science, math, sciences, or a related field.
Experience with search, recommendation, natural language processing, or other large-scale ML systems.
Proven ability to design, build, and ship production-ready models and systems.
Demonstrated expertise in ML evaluation, benchmarking, and data quality—ideally with experience in building or maintaining evaluation frameworks for complex enterprise tasks.
Proficiency in your ML framework of choice (e.g., TensorFlow, PyTorch).
Strong coding skills (Python, Go, Java, C++, etc.).
Thrive in a customer-focused, cross-functional environment; a proactive and positive attitude is a must.

Responsibilities

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.