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Machine Learning Engineer, AI Assistant & Autonomous AI Agents

Glean
G
apartmentGleanlocation_onSan Francisco Bay Area (Hybrid: 3-4 days a week in one of our SF Bay Area offices)schedulePosted 9 days ago
Full-timeMachine Learning EngineerAI AssistantAutonomous AI AgentsLLM$240,000 - $300,000

About the Role

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 looking for senior engineers who will provide expert-level individual contributions and thought leadership to help us build the next generation of intelligent enterprise AI assistants and autonomous AI agents. We are reimagining how LLMs and agents can reason, plan, and act to solve complex, multi-step enterprise workflows. You will work at the intersection of applied research and production engineering in areas such as agentic frameworks, LLM orchestration, low latency LLM inference and optimization, domain adapted and memory augmented LLMs, reinforcement learning, building evaluation frameworks for complex enterprise tasks. We work closely with our customers, deeply understand their pain points, and use the right mix of research-driven and pragmatic engineering approaches to solve them.

Responsibilities

  • Build frameworks for LLM-powered agents to use tools and knowledge sources effectively
  • Invent new agentic architectures and signals to improve reasoning, planning, and personalization in workplace AI assistants
  • Design and optimize reinforcement learning and fine-tuning approaches to improve the quality of agentic systems
  • Lead development of scalable evaluation, benchmarking, and optimization loops for agents in production
  • Drive technical strategy and mentor other engineers, raising the technical bar across the team
  • Write robust, maintainable, and well-tested code that powers enterprise-grade assistants and agents

Requirements

  • 2+ years as a Staff Engineer, Principal Engineer, or equivalent
  • 5+ years of industry experience in AI or Machine Learning Engineering
  • Experience working with agentic frameworks, reinforcement learning, natural language processing, or other large systems involving machine learning
  • Proven ability to design, build, and ship production-ready systems
  • 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
  • A proactive and positive attitude to lead, learn, troubleshoot, and take ownership of both small tasks and large features

Qualifications

N/A

Benefits

  • The standard base salary range for this position is $240,000 - $300,000 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.
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AI Agent DeveloperSan Francisco Bay Area (Hybrid: 3-4 days a week in one of our SF Bay Area offices)

Frequently Asked Questions

How do I apply for this Machine Learning Engineer, AI Assistant & Autonomous AI Agents position?

Click the "Apply Now" button on this page to be directed to the application. You will be taken to the employer's application page.

Is this position remote?

This role is based in San Francisco Bay Area (Hybrid: 3-4 days a week in one of our SF Bay Area offices). Check the full description for remote or hybrid options.

What is the salary range?

The listed salary range for this position is $240,000 - $300,000. Final compensation may vary based on experience, qualifications, and location.

When was this job posted?

This position was posted 9 days ago. We recommend applying promptly as positions can fill quickly.

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