Machine Learning Engineer in Belfast

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? We are seeking a Machine Learning Engineer to join the Data Science Machine Learning team, where you will design, build, and deploy intelligent systems that solve complex business problems across Financial Services, Manufacturing, Energy Utilities, and other commercial industries. This isn't a research role or a support function - you will own the full ML solution lifecycle from problem definition through production deployment.

You will 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 build an agentic demand forecasting system for a global manufacturer, deploy an intelligent knowledge processing pipeline for a financial services firm, and architect an energy grid demand simulation model for a utilities company. If you thrive on learning new domains quickly and shipping intelligent production systems, this role is for you!

Your Role:

• Design and build end-to-end ML solutions - from data pipelines and feature engineering through model training, evaluation, and production deployment. You own the outcome, not just a piece of it.
• Develop 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.
• Create production-grade APIs and services (FastAPI, Flask, or similar) that integrate ML capabilities into client systems and workflows.
• Implement MLOps practices - CI/CD pipelines, model versioning, monitoring, drift detection, and automated retraining to ensure solutions remain reliable in production.
• Collaborate directly with clients to understand business problems, translate requirements into technical solutions, and communicate results to both technical and executive audiences.

The Profile We're Looking For:

• Education: Bachelors Degree in Computer Science, Engineering, Mathematics, Physics, or related quantitative field (or equivalent practical experience). Masters Degree or PhD preferred.
• Experience: 2+ 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.
• Background Industry Experience: Consulting experience or a demonstrated ability to work across multiple domains, and to adapt quickly to new problem spaces. Experience in Financial 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. We are 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.
• Onsite Engagement: The role is primarily based in Belfast, although you may travel to client sites periodically for critical, high-impact project milestones.
• 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.

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: Associate or Senior Associate

Skills: Python, JavaScript, Machine Learning, SQL, Snowflake, Azure, Databricks

Benefits: Healthcare, Dental, Bonus, Hybrid, Travel, Income Protection