Machine Learning Engineer, Assistant Quality
San Francisco, CA
- Pay
$180,000–205,000/year · Base — pay source
Compensation & Benefits: The standard base salary range for this position is $180,000 - $205,000 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.
Read the full posting- Work setup
Hybrid stated — work setup source
Location: This role is hybrid (4 days a week in our San Francisco office) Compensation & Benefits:
Read the full posting- Employment
- Unconfirmed
What you’ll work on
Full postingGlean is seeking a Machine Learning Engineer to improve the quality of our AI Assistant and autonomous agents.
Build and improve ML and LLM-powered systems that raise the quality of Glean’s AI Assistant and autonomous agents across real user workflows.
You will work on applied problems across agent quality, evaluation, personalization, retrieval, and orchestration.
From the employer’s posting
Glean is seeking a Machine Learning Engineer to improve the quality of our AI Assistant and autonomous agents. This role sits at the intersection of production machine learning, LLM-powered systems, and product engineering, with a focus on building, evaluating, and iterating on assistant experiences that are useful, reliable, and grounded in real enterprise workflows. You will work on applied problems across agent quality, evaluation, personalization, retrieval, and orchestration. The ideal person is excited by shipping production systems, not pure research, and wants to help shape how Glean’s assistant gets better over time through stronger signals, tighter feedback loops, and better end-to-end execution quality.
Build and improve ML and LLM-powered systems that raise the quality of Glean’s AI Assistant and autonomous agents across real user workflows.
About the Role: Glean is seeking a Machine Learning Engineer to improve the quality of our AI Assistant and autonomous agents. This role sits at the intersection of production machine learning, LLM-powered systems, and product engineering, with a focus on building, evaluating, and iterating on assistant experiences that are useful, reliable, and grounded in real enterprise workflows. You will work on applied problems across agent quality, evaluation, personalization, retrieval, and orchestration. The ideal person is excited by shipping production systems, not pure research, and wants to help shape how Glean’s assistant gets better over time through stronger signals, tighter feedback loops, and better end-to-end execution quality. You will:
What you’ll bring
All qualificationsCore experience
- 2+ years of industry experience in machine learning, applied AI, or software engineering with significant ML ownership.
- Experience in one or more of the following areas: LLM applications, NLP, search, retrieval, recommendations, evaluation frameworks, agent systems, or personalization.
- Proficiency in common ML tooling and strong software engineering fundamentals in languages such as Python, Go, Java, or C++.
Qualification wording
2+ years of industry experience in machine learning, applied AI, or software engineering with significant ML ownership.
Experience in one or more of the following areas: LLM applications, NLP, search, retrieval, recommendations, evaluation frameworks, agent systems, or personalization.
Proficiency in common ML tooling and strong software engineering fundamentals in languages such as Python, Go, Java, or C++.
Tools in this posting
- Go
- Java
- Python
- C++
Source — Tool mentions in context
- Comfort working across both modeling and product engineering details, including experimentation, quality measurement, and production iteration. - Proficiency in common ML tooling and strong software engineering fundamentals in languages such as Python, Go, Java, or C++. - A pragmatic, product-minded approach. You know when to use sophisticated ML techniques and when simple, reliable systems are the better answer.
Benefits in the posting
Full benefits wording- The standard base salary range for this position is $180,000 - $205,000 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.
- AI-First Mindset at Glean:
- 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.
From the employer’s posting.
About Glean
Glean is the Work AI platform that helps everyone work smarter with AI.
In the employer’s words · Read in context
Job description
You will work on applied problems across agent quality, evaluation, personalization, retrieval, and orchestration. The ideal person is excited by shipping production systems, not pure research, and wants to help shape how Glean’s assistant gets better over time through stronger signals, tighter feedback loops, and better end-to-end execution quality.
- Build and improve ML and LLM-powered systems that raise the quality of Glean’s AI Assistant and autonomous agents across real user workflows.
- Design evaluation, benchmarking, and monitoring loops to measure assistant quality, model quality, and end-to-end system performance.
- Develop and iterate on signals, prompts, workflows, and model-driven logic that improve reasoning, planning, personalization, and task completion quality.
- Work across areas such as RAG, semantic search, recommendation-style systems, post-training or reinforcement learning, and agent orchestration where they materially improve product outcomes.
- Partner closely with product, design, and engineering teammates to understand customer pain points and ship high-quality production systems quickly.
- Contribute to the data and ML infrastructure needed to support robust experimentation, offline and online evaluation, and continuous model improvement.
- 2+ years of industry experience in machine learning, applied AI, or software engineering with significant ML ownership.
- Strong hands-on coding ability and a track record of shipping production systems, not just prototypes or research projects.
- Experience in one or more of the following areas: LLM applications, NLP, search, retrieval, recommendations, evaluation frameworks, agent systems, or personalization.
- Comfort working across both modeling and product engineering details, including experimentation, quality measurement, and production iteration.
- Proficiency in common ML tooling and strong software engineering fundamentals in languages such as Python, Go, Java, or C++.
- A pragmatic, product-minded approach. You know when to use sophisticated ML techniques and when simple, reliable systems are the better answer.
- A proactive, low-ego working style and excitement about learning quickly in a high-velocity environment.
- This role is hybrid (4 days a week in our San Francisco office)
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.
Your next step
- Have your CV and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
Complete your application on job-boards.greenhouse.io. The employer’s form will show what is required.
Already applied? Track this application
Source & posting history
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
Compensation & Benefits: The standard base salary range for this position is $180,000 - $205,000 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.
- Location & working pattern
San Francisco, CA
Location: - This role is hybrid (4 days a week in our San Francisco office) Compensation & Benefits:
More source context
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:
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
- Status in our records
- Active
- First seen by us
- Aug 5, 2026
- Recorded sightings
- 46
- Last seen by us
- Oct 7, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
Report an errorSee how this role fits your experience
Add your resume to compare the role’s scope, tools and requirements with your experience.