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Machine Learning Research Engineer

Decagon • Full-time • San Francisco, CA, US • $250k - $415k / year • 1m ago

About Decagon

Decagon is the leading conversational AI platform empowering every brand to deliver concierge customer experience. Our AI agents provide intelligent, human-like responses across chat, email, and voice, resolving millions of customer inquiries across every language and at any time.

Since coming out of stealth, Decagon has experienced rapid growth. We partner with industry leaders like Hertz, Eventbrite, Duolingo, Oura, Bilt, Curology, and Samsara to redefine customer experience at scale. We've raised over $200M from Bain Capital Ventures, Accel, a16z, BOND Capital, A*, Elad Gil, and notable angels such as the founders of Box, Airtable, Rippling, Okta, Lattice, and Klaviyo.

We’re an in-office company, driven by a shared commitment to excellence and velocity. Our values—customers are everything, relentless momentum, winner’s mindset, and stronger together—shape how we work and grow as a team.

About The Team

The Research team at Decagon innovates on building the most advanced conversational AI agents for enterprise customers. Decagon’s AI agents understand context, respond with genuine empathy, and solve complex problems with surgical precision.

Our mission is to deliver magical support experiences — AI agents working alongside human agents to help users resolve their issues.

About The Role

On the Research team, you’ll be responsible for building AI systems that can perform previously impossible tasks or achieve unprecedented levels of performance. You will design and implement state of the art methods for instruction tuning and information retrieval. We're looking for people with strong engineering skills, writing bug-free machine learning code, and building the science behind the algorithms that power our AI agents.

Engineers here own their work end-to-end and are trusted to make a real impact. This role is for someone who dives deep into complex system challenges, builds elegant solutions that scale to millions of users, and creates automation that prevents problems before they happen.

In this role, you will

Develop models for customer support tasks that exceed the performance of closed source models
Experiment with small open-source models to drive order of magnitude reductions in latency across channels
Break down ambiguous research ideas into clear, iterative milestones and roadmaps.

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