Why This Job is Featured on The SaaS Jobs
Work on an “Enterprise Brain” product sits at a clear inflection point in SaaS: application-layer AI that has to operate across many tools, documents, and workflows inside large organizations. The listing signals a SaaS environment where search, knowledge graphs, ranking, and LLM-driven agents converge, which is increasingly central to how enterprise software is being rebuilt. The hybrid Bay Area setup also suggests close coupling between research, product decisions, and production constraints rather than a purely experimental ML lab.
For a long-term SaaS career, this kind of role builds durable instincts around reliability and measurement in ML systems that ship. Emphasis on evaluation loops, benchmarking, data quality, and end-to-end monitoring maps directly to the realities of SaaS: continuous releases, changing customer data, and the need to prove improvements with repeatable metrics. Experience spanning orchestration, fine-tuning, and scalable pipelines is broadly transferable across AI-first SaaS teams working on personalization, automation, or enterprise search.
This role fits engineers who like bridging model work with operational rigor, and who prefer owning quality outcomes rather than optimizing isolated components. It also suits practitioners comfortable collaborating cross-functionally to translate enterprise pain points into measurable system behavior, especially in environments where production readiness matters as much as novelty.
The section above is editorial commentary from The SaaS Jobs, provided to help SaaS professionals understand the role in a broader industry context.
Job Description
About the Role:
Glean is seeking a few Machine Learning engineers who want to focus on a combination of Quality and traditional ML work to help us build the Enterprise Brain. The Enterprise Brain team is developing a suite of proactive AI products that aims to revolutionize enterprise workflows by proactively detecting and automating tasks for users - thus unlocking true productivity. This is built on top of a deep user understanding and state of the art Enterprise graph. The project involves using both LLM and other advanced ML techniques, agent orchestration and cutting-edge ranking techniques.
You will:
- 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, prediction and other 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.
About you:
- 3+ years of industry experience in AI or Machine Learning Engineering.
- BA/BS in computer science, math, sciences, or a related field.
- Experience with search, recommendation, natural language processing, 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 in building or maintaining evaluation frameworks for complex enterprise tasks.
- Proficiency in your ML framework of choice (e.g., TensorFlow, PyTorch).
- Strong coding skills (Python, Go, Java, C++, etc.).
- Thrive in a customer-focused, cross-functional environment; a proactive and positive attitude is a must.
Location:
- This role is hybrid (4 days a week in our Palo Alto or SF offices)
Compensation & Benefits:
The standard base salary range for this position is $200,000 - $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.
We are a diverse bunch of people and we want to continue to attract and retain a diverse range of people into our organization. We're committed to an inclusive and diverse company. We do not discriminate based on gender, ethnicity, sexual orientation, religion, civil or family status, age, disability, or race.
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