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DecagonDecagonSan Francisco, CA

Research Engineer

Research Engineer building and deploying production conversational AI models and agents at Decagon. Improve instruction following, retrieval, memory, and long-horizon task completion; take research prototypes to measurable production impact using LLMs and ML tooling.

200k – 400k/yr
On-site2+ YOEML Engineering

About the role

Responsibilities

  • Lead research and engineering efforts 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 that optimize 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.
  • Build industry-leading conversational AI models that power Decagon’s agent, taking them from idea to production.
  • Own multi-quarter initiatives that push the agent’s reliability, capability, and efficiency forward.
  • Design and implement frontier approaches for training, evaluation, and orchestration across the system.

Requirements

  • 2+ 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 to reliable, measurable production impact.

Compensation

$200K – $400K + 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, with flexibility for candidates who demonstrate exceptional impact. In addition to base salary, we offer competitive equity.

Skills

PythonLLMsMachine Learningpost-trainingmodel deploymenttraining pipelinesevaluation pipelinesData Pipelinesretrievalmemory systems

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