Why This Job is Featured on The SaaS Jobs
This Machine Learning Engineer role sits at the heart of a SaaS product where search quality is a primary differentiator: helping knowledge workers find and use information across customer-specific corpora. The scope spans query and document understanding, ranking, and domain-adapted language models, which reflects a mature, product-led approach to applied ML rather than isolated research.
For a SaaS career, the role offers durable experience in building production ML systems that must be evaluated, iterated, and maintained over time. Work on personalization signals, ranking interactions, and LLM plus search techniques maps directly to common SaaS challenges such as relevance, trust, and measurable product impact. Regular customer interaction also builds the habit of grounding model work in real usage constraints, a skill that transfers across enterprise and horizontal SaaS categories.
This position is best suited to engineers who like end-to-end ownership, from data and modeling choices through to robust implementation and testing. It will appeal to professionals who prefer applied problem solving over purely theoretical work, and who are comfortable collaborating across functions while using experimentation to make tradeoffs explicit.
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 engineers to help build the world’s best search and assistant product for work. Our engineers work on a range of systems across the stack, including query understanding, document understanding, domain-adapted language models, natural language question-answering, evaluation, and experimentation. We interact regularly with customers, deeply understand their pain points, and use whatever tool is necessary, simple or complex, to solve their problems.
You will:
- Invent new signals to improve the personalization of our search engine
- Train a model to capture interactions between signals in our ranking system
- Design smarter ways to domain-adapt language models to each customer’s corpus
- Discover new ways of combining LLMs with search engines to answer complex questions
- Write robust code that’s easy to read, maintain, and test
- Mentor more junior engineers, or learn from battle-tested ones
About you:
- 2+ years of experience
- BA/BS in computer science, math, sciences, or a related degree
- Experience working with search, recommendation, natural language processing, or other large systems involving machine learning
- Strong analytical skills and ability to work with data
- Proven ability to design, build, and ship production-ready models
- 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 is a must
- 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 $140,000 - $265,000 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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