Huron is a global consultancy that collaborates with clients to drive strategic growth, ignite innovation and navigate constant change. We are looking for a hands-on and adaptable AI/ML Engineer to join our AI practice, where you will design, build, and deploy intelligent systems leveraging machine learning and generative AI technologies.
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 mechanisms to monitor AI system behavior, including accuracy, drift, reliability, and task-level reasoning
- Collaborate with software engineers, data scientists, and solution architects to ensure seamless design, development, and transition to production
- Support rapid experimentation as well as robust deployment pipelines, depending on the maturity of each use case
- Stay informed on the latest trends in GenAI, AI agents, orchestration protocols, and evaluation frameworks to continuously evolve our capabilities
- Support project management tasks, including planning, tracking deliverables, coordinating cross-functional teams, and ensuring alignment with client timelines and objectives
- Assist in preparing status reports, managing stakeholder communications, and identifying risks or issues in project execution
Requirements:
- 3+ years of hands-on experience in AI/ML development or intelligent application engineering
- Bachelor's degree in Computer Science, Engineering, Data Science, or a related field
- Experience in Python
- Familiarity with modern ML/AI libraries (e.g., scikit-learn, PyTorch, TensorFlow, OpenAI APIs)
- Familiarity with cloud platforms (Azure, AWS) and containerization tools (Docker)
- 5+ years of hands-on experience in AI/ML development or intelligent application engineering
- Proficiency in Python
- Strong familiarity with modern ML/AI libraries (e.g., scikit-learn, PyTorch, TensorFlow, OpenAI APIs)
- Experience building APIs or backend services using FastAPI, Flask, or equivalent frameworks
- Exposure to agent frameworks (e.g., LangGraph, AutoGen) and vector databases
- Strong Familiarity with cloud platforms (Azure, AWS) and containerization tools (Docker)
- Familiarity with cloud-based ML platforms such as Azure Machine Learning, AWS SageMaker, or Google AI/ML services
- Experience with MLOps pipelines, CI/CD for model delivery, or model monitoring is a plus
- Familiarity with orchestration standards or tools such as MCP or agent routing protocols is a plus
- Knowledge of AI system evaluation, observability, or prompt performance testing is a plus
- Ability to work on cross-functional teams, balance multiple projects, and communicate effectively with technical and non-technical audiences
- Cloud certifications in AI/ML services (Azure, AWS, or Google Cloud) is a plus
- Experience managing technical projects or performing hybrid engineer/PM roles, with strong organizational and communication skills
- Ability to balance hands-on development with project coordination, ensuring both technical quality and timely delivery