Why This Job is Featured on The SaaS Jobs
This Machine Learning Engineer role sits squarely in the current wave of SaaS products being rebuilt around enterprise AI. The focus on an “Enterprise Brain” implies a platform layer that must work across messy, permissioned corporate knowledge, where search, ranking, and personalization become core product capabilities rather than supporting features. For SaaS professionals, that combination of LLM workflows, agent orchestration, and enterprise graph signals points to problems that are difficult specifically because they must operate reliably at scale for business users.
The long-term career value comes from working on end-to-end ML quality in a product setting, not just model prototyping. Building evaluation loops, benchmarking, monitoring, and data quality practices maps directly to how modern SaaS teams ship AI features responsibly. Experience here tends to transfer across AI-first SaaS companies because the same disciplines recur: measurable relevance, feedback-driven iteration, and production-grade pipelines tied to user outcomes.
This role is best suited to engineers who like ambiguity framed by metrics and who enjoy pairing research-informed techniques with pragmatic systems work. It also fits those who want cross-functional exposure, since enterprise AI requires tight alignment with product and customer realities, especially around reliability and trust.
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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