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Software Engineer, Machine Learning (Infrastructure)

San Francisco Bay Area
About Glean:
 
Founded in 2019, Glean is an innovative AI-powered knowledge management platform designed to help organizations quickly find, organize, and share information across their teams. By integrating seamlessly with tools like Google Drive, Slack, and Microsoft Teams, Glean ensures employees can access the right knowledge at the right time, boosting productivity and collaboration. The company’s cutting-edge AI technology simplifies knowledge discovery, making it faster and more efficient for teams to leverage their collective intelligence.
 
Glean was born from Founder & CEO Arvind Jain’s deep understanding of the challenges employees face in finding and understanding information at work. Seeing firsthand how fragmented knowledge and sprawling SaaS tools made it difficult to stay productive, he set out to build a better way - an AI-powered enterprise search platform that helps people quickly and intuitively access the information they need. Since then, Glean has evolved into the leading Work AI platform, combining enterprise-grade search, an AI assistant, and powerful application- and agent-building capabilities to fundamentally redefine how employees work.

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 generative AI, RAG, 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:

  • Design, build, and improve ML systems and Data pipelines infrastructure
  • Work with and enable other ML engineers focused on modeling
  • Write robust code that’s easy to read, maintain, and test
  • Mentor more junior engineers, or learn from battle-tested ones

About you:

  • 5+ years of experience
  • BA/BS in computer science, math, sciences, or a related degree
  • Experience working with ML infrastructure and engineering for search, recommendation, natural language processing, or something similar
  • Proven ability to design, build, and ship production-ready software, ideally around ML infrastructure (pipelines, serving, GenAI)
  • Strong Experience working with Apache Spark and hands-on experience with building, scaling, and operating large batch data pipelines
  • 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 $200,000 - $280,000 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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