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GustoGustoDenver, CO

Staff Applied AI Scientist

Designs, builds, and scales AI platform infrastructure including agent orchestration, RAG, eval tooling, and model serving for internal teams. Requires 12+ years AI/ML experience, expertise in LLMs/NLP, Python proficiency, and ML frameworks like PyTorch.

245k – 321k/yr
Hybrid12+ YOEML Engineering

About the role

Responsibilities

  • Design and build scalable platform services — agent orchestration, RAG pipelines, eval frameworks, model serving — that internal teams use to ship AI-powered products.
  • Lead technical strategy and architecture for the AI platform, including model lifecycle, observability, safety guardrails, and evaluation infrastructure.
  • Collaborate cross-functionally with app teams, PMs, and Designers to understand their AI needs and deliver platform capabilities that unblock them.
  • Build, harden, and operate shared infrastructure that powers intelligent agents across Gusto (e.g., retrieval, routing, prompt management, content selection).
  • Stay current with AI/ML research; rapidly prototype and productionize new techniques that strengthen the platform.
  • Establish robust practices for validation, deployment, monitoring, and ongoing performance management of platform services and the agents built on them.
  • Communicate technical strategy, tradeoffs, and impact clearly to executives and non-technical partners.
  • Mentor engineers across teams, raising the bar on AI/ML best practices and fostering a culture of pragmatic innovation.

Requirements

  • 12+ years building and deploying end-to-end AI/ML systems, with experience designing platform-level infrastructure that other engineering teams build on.
  • Deep expertise in one or more areas: LLMs, NLP, retrieval/RAG, agent orchestration, deep learning, or reinforcement learning.
  • Hands-on experience building LLM-based applications and agentic workflows — including prompt engineering, retrieval design, evaluation, and production deployment.
  • Proficiency with modern ML frameworks (PyTorch, TensorFlow, Hugging Face) and cloud platforms (GCP, AWS, or Azure).
  • Strong Python skills and sound software engineering fundamentals — testing, code review, CI/CD, reliability, and API design.
  • Proven track record shipping impactful AI/ML projects to production, ideally in a platform or infrastructure context.
  • Demonstrated ability to lead cross-functionally, influence technical direction, and communicate clearly with both engineers and non-technical stakeholders.

Nice-to-Haves

  • Ph.D. or Master's in CS, ML, Statistics, Mathematics, or related field.

Compensation

  • Targeted at $245,000-272,000 in Denver & most remote locations.
  • $288,000-321,000 for San Francisco & New York.

Skills

LLMsNLPRAGAgent OrchestrationPyTorchTensorFlowHugging FacePythonGCPAWS

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