Why This Job is Featured on The SaaS Jobs
Within the SaaS ecosystem, this Machine Learning Engineer role sits at the point where enterprise software is being reshaped by LLM-powered assistants and agentic workflows. The remit spans both applied research and production engineering, a combination that matters in SaaS because enterprise customers expect reliability, latency, and security characteristics that pure research prototypes rarely meet. The Bay Area hybrid setup also signals close iteration with stakeholders when product behavior and model performance need tight feedback loops.
For a long-term SaaS career, the role offers durable leverage in three areas that consistently transfer across companies: turning ambiguous workflow problems into measurable ML objectives, building evaluation systems that keep quality stable as products evolve, and shipping model-driven features with clear operational constraints. Experience with orchestration, inference optimization, and reinforcement learning in production maps directly to how SaaS teams industrialize AI capabilities rather than treating them as one-off demos.
This position fits senior ICs who prefer owning technical direction through systems design, benchmarking, and pragmatic tradeoffs, while still engaging with emerging techniques. It will suit engineers who like cross-functional problem framing and can move between customer context, model behavior, and software architecture without over-indexing on any single layer.
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 looking for senior engineers who will provide expert-level individual contributions and thought leadership to help us build the next generation of intelligent enterprise AI assistants and autonomous AI agents. We are reimagining how LLMs and agents can reason, plan, and act to solve complex, multi-step enterprise workflows. You will work at the intersection of applied research and production engineering in areas such as agentic frameworks, LLM orchestration, low latency LLM inference and optimization, domain adapted and memory augmented LLMs, reinforcement learning, building evaluation frameworks for complex enterprise tasks. We work closely with our customers, deeply understand their pain points, and use the right mix of research-driven and pragmatic engineering approaches to solve them.
You will:
- Build frameworks for LLM-powered agents to use tools and knowledge sources effectively
- Invent new agentic architectures and signals to improve reasoning, planning, and personalization in workplace AI assistants
- Design and optimize reinforcement learning and fine-tuning approaches to improve the quality of agentic systems
- Lead development of scalable evaluation, benchmarking, and optimization loops for agents in production
- Drive technical strategy and mentor other engineers, raising the technical bar across the team
- Write robust, maintainable, and well-tested code that powers enterprise-grade assistants and agents
About you:
- 2+ years as a Staff Engineer, Principal Engineer, or equivalent
- 5+ years of industry experience in AI or Machine Learning Engineering
- Experience working with agentic frameworks, reinforcement learning, natural language processing, or other large systems involving machine learning
- Proven ability to design, build, and ship production-ready systems
- Proficiency in your ML framework of choice
- Strong coding skills (Python, Go, Java, C++, ...)
- Thrive in a customer-focused, tight-knit and cross-functional environment - being a team player and willing to take on whatever is most impactful for the company
- A proactive and positive attitude to lead, learn, troubleshoot, and take ownership of both small tasks and large features
Location:
- This role is hybrid (3-4 days a week in one of our SF Bay Area offices)
Compensation & Benefits:
The standard base salary range for this position is $240,000 - $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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