Machine Learning Engineer, Enterprise Brain

Glean Technologies is hiring Machine Learning engineers for its Enterprise Brain team to develop proactive AI capabilities. The work focuses on detecting and automating user tasks using the Enterprise graph, combining evaluated production ML with advanced ML and LLM techniques.

Role Responsibilities

• Address complex ML problems related to user understanding and task prediction.
• Develop new LLM workflows and signals to enhance reasoning, planning, and personalization.
• Design and improve reinforcement learning and fine-tuning approaches to raise the quality of understanding, prediction, and other agentic systems.
• Lead the creation of scalable evaluation, benchmarking, and optimization loops.
• Build and maintain reliable ML pipelines for enterprise and knowledge graph construction.
• Measure, monitor, and improve data quality, model quality, and end-to-end system performance.
• Partner with cross-functional teams to translate customer pain points into high-quality, production-ready ML solutions.
• Mentor junior engineers, and collaborate in a tight-knit, high-velocity environment where knowledge sharing flows both ways.

Requirements

• 6+ years of industry experience in machine learning engineering.
• BA/BS in computer science, math, sciences, or a related field.
• Proven ability to design, build, and ship production-ready models and systems.
• Demonstrated expertise in ML evaluation, benchmarking, and data quality.
• Proficiency in an ML framework such as TensorFlow or PyTorch.
• Comfort operating in a fast-moving, ambiguous setting by converting open-ended problems into clear priorities and production-ready work.
• Experience balancing speed with quality through pragmatic tradeoffs that maintain production readiness while delivering measurable progress.

Technologies

• TensorFlow
• PyTorch

Compensation and Benefits

Base Salary Range: USD 200,000 - 280,000 per year.

Compensation is determined based on factors including location, level, and job-related knowledge, skills, and experience. Some roles may be eligible for variable compensation, equity, and benefits.

• Comprehensive benefits package
• Medical coverage
• Vision coverage
• Dental coverage
• Generous time-off policy
• Opportunity to contribute to your 401k plan
• Home office improvement stipend
• Annual education and wellness stipends
• Regular events
• Healthy lunches daily

Location and Work Model

The position is hybrid, with 4 days per week in the Mountain View office.

AI-First Mindset at Glean

As part of the interview process, you will complete a brief AI-focused exercise or discussion to explain how you think about, design, and use AI to drive impact in your role. You may reference any tools, platforms, or workflows you use today; prior Glean experience is not required.

Global Data Privacy Notice for Job Candidates and Applicants

• Depending on your location, GDPR, CCPA, or other privacy laws may regulate how applicant data is managed.
• The full notice outlining how data is processed as part of the application procedure is available in the Privacy Policy.
• By submitting your application, you agree to the use and processing of your data as required.
• US applicants and their applications are subject to arbitration of disputes as outlined in the Applicant Arbitration Agreement.