Machine Learning Engineer, Enterprise Brain
About The Position
Glean’s Enterprise Brain team builds applied machine learning systems that help Glean understand users’ work and anticipate useful next steps, including task prediction and proactive assistance. The work combines LLMs and traditional ML with Enterprise Graph signals, ranking and retrieval, and orchestration. The Machine Learning Engineer owns production ML problems from problem definition and evaluation through launch and monitoring, with a focus on measurable improvements to product quality. The role involves building and shipping production systems, creating evaluation, benchmarking, and data-quality loops, and partnering with product and engineering teams to deliver reliable, production-ready solutions. This is a hybrid role requiring four days per week in Glean’s Mountain View office. The standard base salary range is $200,000–$280,000 annually. Compensation may also include variable compensation, equity, and benefits depending on the role and other factors.
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.
- Ability to thrive in a fast-moving, ambiguous environment and turn open-ended customer and ML problems into clear priorities and production-ready solutions.
- Ability to balance speed with quality and make pragmatic tradeoffs while delivering measurable progress and maintaining production readiness.
Responsibilities
- Define and solve applied ML problems involving user-work understanding, task prediction, and proactive assistance.
- Combine LLMs and traditional ML with Enterprise Graph signals, ranking and retrieval, and orchestration to improve product quality.
- Build and ship production ML systems, including evaluation, benchmarking, and data-quality loops to measure impact.
- Own the lifecycle from problem definition and baseline through launch, monitoring, and iteration.
- Partner with product and engineering to understand customer problems and deliver reliable, production-ready solutions.
Benefits
- Medical, vision, and dental coverage.
- Generous time-off policy.
- Opportunity to contribute to a 401(k) plan.
- Home office improvement stipend.
- Annual education stipend.
- Annual wellness stipend.
- Regular company events.
- Healthy lunches daily.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
