Job Details

Machine Learning Engineer, Enterprise Brain

  2025-11-28     Glean Technologies     San Francisco,CA  
Description:

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.

Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map relationships between people, content, and activity, delivering deeply personalized, context‑aware responses for every employee. This foundation powers AI agents that automate real work across teams by accessing the industry's broadest range of data—structured, unstructured, historical, and real‑time. The result: measurable business impactthrough faster onboarding, hours of productivity gained each week, and smarter,safer decisions at every level.

Recognized by Fast Company, CNBC, Bloomberg, Forbes, and Gartner, Glean has customers across 50+ industries and 1,000+ employees in more than 25 countries.

About the Role

Glean is seeking Machine Learning engineers focused on Quality and traditional ML workto help build the Enterprise Brain—proactive AI products that detect and automate tasks for users, unlocking true productivity. The role combines LLM, advanced ML techniques,agent orchestration, and cutting‑edge ranking.

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 and prediction for 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.

Qualifications

  • 3+ years of industry experience in AI or Machine Learning Engineering.
  • BA/BS in computer science, math, sciences, or related field.
  • Experience with search, recommendation, NLP, 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 building evaluation frameworks for enterprise tasks.
  • Proficiency in your ML framework of choice (e.g., TensorFlow, PyTorch).
  • Thrive in a customer‑focused, cross‑functional environment; a proactive and positive attitude is a must.

Location & Remote Options

  • This role is hybrid: 4 days a week in our Palo Alto or SF offices.

Compensation & Benefits

The base salary range for this position is $200,000 – $300,000 annually. Compensation is determined by location, level, job‑related skills, and experience. Certain roles may qualify for variable compensation, equity, and benefits.

We offer a comprehensive benefits package including medical, vision, dental coverage, generous time‑off policy, 401(k) plan, home office improvement stipend, annual education and wellness stipends, healthy lunches, and a vibrant company culture with regular events.

Equal Employment Opportunity

As set forth in Glean's Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law. We are committed to an inclusive and diverse company.

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