Software Engineer, Machine Learning

Glean; Bengaluru; Presencial; INR 1 800 000 - 2 400 000; Tempo integral

Resumo da oferta

Glean is hiring engineers to build the world's best search and assistant product for work, focusing on query understanding, document understanding, and domain-adapted language models. You will interact with customers to understand pain points and solve problems with the right tools, from simple to complex.

The role involves designing, training, and evaluating models, shipping production-ready code, and collaborating with cross-functional teams to drive impact at scale in a mission-driven

Qualificações

• This role requires a BA/BS in CS, math, sciences, or related degree.
• 6+ years of experience in engineering, with focus on search, NLP, or large ML systems.
• Proficiency with ML frameworks and strong data analysis skills.

Responsabilidades

• Invent signals to improve personalization of search.
• Train models to capture interactions in ranking systems.
• Domain-adapt language models to customer corpora.
• Explore combining LLMs with search to answer complex questions.
• Write robust, readable, well-tested code.
• Mentor junior engineers or learn from experienced peers.

Conhecimentos

Search systems

NLP

ML frameworks

Data analysis

Team collaboration

Formação académica

BA/BS in Computer Science or related

Ferramentas

ML frameworks

Descrição da oferta de emprego

Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry's most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles.

At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean's agentic capabilities - AI agents that automate real work across teams by accessing the industry's broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level.

Recognized by Fast Company as one of the World's Most Innovative Companies (Top 10, 2025), by CNBC's Disruptor 50, Bloomberg's AI Startups to Watch (2026), Forbes AI 50, and Gartner's Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we're helping the world's largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality.

If you're excited to shape how the world works, you'll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more - deeply embedded where people get things done. You'll ship agentic capabilities on an open, extensible stack, with the craft and care required for enterprise trust, as we bring Work AI to every employee, in every company.

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:

• 6+ 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
• 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 in person in Bangalore, India

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 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.

At Glean, AI fluency is core to how we work and we're committed to ensuring every new hire feels confident integrating AI into their everyday work. As part of the interview process, you'll complete a brief AI-focused exercise or discussion so we can understand how you think about, design, and use AI to drive impact in your role. Feel free to reference any tools, platforms, or workflows you use today - prior Glean experience isn't required.

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