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. Ready to join our Commercial Digital Practice? Were seeking a Machine Learning Engineering Manager to join the Data Science & Machine Learning team, where youll lead the design, development, and deployment of intelligent systems that solve complex business problems across Financial Services, Manufacturing, Energy & Utilities, and other commercial industries. Managers play a vibrant, integral role at Huron. Their invaluable knowledge reflects in the projects they manage and the teams they lead. Known for building long-standing partnerships with clients, they collaborate with colleagues to solve their most important challenges. Remarkably versatile, our Managers also spend significant time mentoring junior staff on the engagement team - sharing expertise, feedback, and encouragement. This promotes a culture of respect, unity, collaboration, and personal achievement. This isnt a research role or a support function - youll own the full ML solution lifecycle from problem definition through production deployment, while leading and developing a team of engineers and data scientists. Youll work on systems that matter: forecasting models that inform multi-million-dollar decisions, agentic AI systems that automate complex workflows, and operational ML solutions that transform how enterprises run. Our clients are Fortune 500 companies looking for partners who can deliver, not just advise. The variety is real. In your first year, you might lead an agentic demand forecasting system for a global manufacturer, oversee an intelligent knowledge processing pipeline for a financial services firm, and architect an energy grid demand simulation model for a utilities company - all while developing the next generation of ML talent at Huron! If you thrive on learning new domains quickly, shipping intelligent production systems, and building high-performing teams, this role is for you. Your Role:Machine Learning Manager Lead and mentor junior ML engineers and data scientists, including providing technical guidance, conducting code reviews, and supporting professional development. Manage complex multi-workstream ML projects, including overseeing project planning, resource allocation, and delivery timelines. Ensure projects meet quality standards and client expectations while maintaining technical excellence. Design and architect end-to-end ML solutions, from data pipelines and feature engineering through model training, evaluation, and production deployment. Make key technical decisions and own the overall solution architecture. Lead development of both traditional ML and generative AI systems, including supervised/unsupervised learning, time-series forecasting, NLP, LLM applications, RAG architectures, and agent-based systems using frameworks like Agent Framework, LangChain, LangGraph, or similar. Build financial and operational models that drive business decisions - demand forecasting, pricing optimization, risk scoring, anomaly detection, and process automation for commercial enterprises. Establish MLOps best practices - define and implement CI/CD pipelines, model versioning, monitoring, drift detection, and automated retraining standards to ensure solutions remain reliable in production. Serve as a trusted advisor to clients by building long-standing partnerships, understanding business problems, translating requirements into technical solutions, and communicating results to both technical and executive audiences. Contribute to practice development by participating in business development activities, developing reusable assets and methodologies, and helping to shape the technical direction of Hurons DSML capabilities. The Profile Were Looking For: The skills/background you will need to succeed include: Education:Bachelors Degree in Computer Science, Engineering, Mathematics, Physics, or related quantitative field (or equivalent practical experience). Masters Degree or PhD preferred. Experience:5+ years of hands-on experience building and deploying ML solutions in production, not just notebooks and prototypes. You should have experience training models, putting them into production, and maintaining them. Management & Mentorship:Experience leading and developing technical teams to include coaching, mentoring, code review, junior talent development, and performance management. Background & Industry Experience:Consulting experience or a demonstrated ability to work across multiple domains, and to adapt quickly to new problem spaces. Experience inFinancial Services, Manufacturing, or Energy & Utilities industries would be preferred. Programming Skills:Strong Python and JavaScript experience, with deep experience in the ML ecosystem (NumPy, Pandas, Scikit-learn, PyTorch or TensorFlow, etc.), as well as proficiency with JavaScript web app development. Machine Learning Fundamentals Foundation: Supervised and unsupervised learning, model evaluation, feature engineering, hyperparameter tuning, and understanding of when different approaches are appropriate. Cloud Machine-Learning Platforms:Experience working with Azure Machine Learning, with working knowledge of AWS SageMaker or Google AI Platform. Were platform-flexible but Microsoft-preferred. Data Platforms:Proficient with SQL, Snowflake, Databricks, or similar. You should also be comfortable working with large datasets and building data pipelines. Experience with LLMs and generative AI: Prompt engineering, fine-tuning, embeddings, RAG systems, or agent frameworks. You understand both the capabilities and limitations. Client-Facing & Communication Skills:Ability to communicate technical concepts to non-technical stakeholders and work effectively with cross-functional teams. Ability to lead client meetings and build trusted relationships with executive audiences. Onsite Engagement: The role is primarily based in Belfast, although you may travel to client sites periodically for critical, high-impact project milestones. Willingness to travel approximately 30% is required. Certifications: Azure AI Engineer, AWS ML Specialty, or Databricks ML Associate (preferred). Preferred Criteria: Background in forecasting, optimization, or financial modeling applications. Deep Learning Frameworks:Experience with PyTorch, Tensorflow, fastai, DeepSpeed, etc. MLOps Tools Experience:MLflow and Weights & Biases Contributions to open-source projects or familiarity with open-source ML tools and frameworks. Experience building agentic AI systems using Agent Framework (or predecessors), LangChain, LangGraph, CrewAI, or similar frameworks. Equal Opportunity & Compliance Huron is an equal opportunity employer. We are committed to creating an inclusive and diverse workplace. All employment decisions are made without regard to race, colour, religion, gender, sexual orientation, gender identity or expression, national origin, age, disability, or any other legally protected status. In connection with your application, we will process your personal data in accordance with our privacy policy. Position Level:Manager Skills: Python JavaScript Machine Learning SQL Snowflake Azure Databricks Benefits: Healthcare Dental Bonus Hybrid Travel Income Protection
