Senior Research Engineer
Decagon · San Francisco
About this role
## About Decagon Decagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences. Our technology enables industry-defining enterprises like Avis Budget Group, Block’s Cash App and Square, Chime, Oura Health, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel. We’re an in-office company, driven by a shared commitment to excellence and velocity. Our values—**Just Get It Done**, **Invent What Customers Want**, **Winner’s Mindset**, and **The Polymath Principle**—shape how we work and grow as a team. ## About the Team The Research team develops the model and decision-making stack that powers Decagon’s conversational agents for enterprise support. We research, adapt, and implement state-of-the-art techniques in **model training, prompting, orchestration, and evaluation** to make our agents more accurate, robust, and efficient in real-world deployments. ## About the Role (Senior Research Engineer) As a **Senior Research Engineer**, you’ll build industry-leading conversational AI models that power Decagon’s agent—taking them from idea to production. You’ll own multi-quarter initiatives to improve the agent’s **reliability, capability, and efficiency**, and design frontier approaches for **training, evaluation, and orchestration** across the system. You’ll work on core models and algorithms behind our AI agents, owning your work end-to-end and making high-impact technical decisions. ### What you’ll do - **Lead research and engineering** to improve core conversational capabilities in production, including **instruction following, retrieval, memory, and long-horizon task completion** - **Build and iterate** on end-to-end models and pipelines optimizing for **quality, efficiency, and user experience** - **Partner** with platform and product engineers to integrate new models into production systems - **Break down ambiguous research ideas** into clear, iterative milestones and roadmaps ### Your background - **4+ years** of experience in AI/ML engineering or research - Prior experience **post-training and deploying LLMs** in production environments - Fluency in **Python** and modern ML tooling (training, evaluation, data pipelines) - Track record of taking research ideas from **prototype → measurable production impact** ## Compensation **$200K – $400K + Offers Equity** This range reflects the expected compensation for this role. Compensation within the range is determined based on experience, skills, and the scope of responsibilities.
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