AI/ML Engineer (Senior Associate) - Remote

Company: Huron Consulting Group

Location: Chicago, IL (Remote)

Salary: $130,000 - $188,800 a year

Type: Full-time

Remote: Yes

Posted: 2026-03-31

About this role

Huron is a global consultancy that collaborates with clients to drive strategic growth, ignite innovation and navigate constant change. Through a combination of strategy, expertise and creativity, we help clients accelerate operational, digital and cultural transformation, enabling the change they need to own their future.

Join our team as the expert you are now and create your future.

We are looking for a hands-on and adaptable AI/ML Engineer to join our AI practice. You’ll help design, build, and deploy intelligent systems that leverage a range of technologies—from machine learning to generative AI and agent-based architectures—to solve complex, real-world problems.
This role spans the full AI solution lifecycle: data preparation, model development, application integration, and ongoing evaluation. You will collaborate closely with architects, and domain experts to ensure the AI solutions you help build are intelligent, reliable, and aligned with client goals.
We work across industries and use cases, from early-stage prototypes to production-ready deployments, and we're continuously exploring new AI paradigms—including AI agents, agent orchestration layer, model chaining, and self-evaluating systems. If you’re excited by emerging AI technologies, fast-moving teams, and applied problem-solving, this is the role for you.

Key Responsibilities

  • Design and develop AI-powered systems using both traditional ML and generative AI techniques, including prompt engineering, fine-tuning, and embeddings
  • Build intelligent applications and agents that can perform tasks autonomously or interactively, using frameworks like LangGraph, AutoGen, CrewAI or similar
  • Create modular, well-documented APIs and service components (e.g., using FastAPI or Flask) to enable model integration and consumption
  • Develop and manage data pipelines, including data collection, transformation, and quality assurance to support model training
  • Implement observability and evaluation mec...

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