At a Glance
- Tasks: Design and deploy intelligent ML systems that solve real business problems.
- Company: Join Huron, a global consultancy driving innovation and transformation.
- Benefits: Competitive salary, health coverage, remote work options, and continuous learning opportunities.
- Why this job: Make a measurable impact with Fortune 500 clients using cutting-edge AI technologies.
- Qualifications: Experience in ML solutions, strong programming skills, and a passion for problem-solving.
- Other info: Dynamic team environment with significant career growth potential.
The predicted salary is between 28800 - 48000 ÂŁ per year.
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 seeking a Machine Learning Engineer to join the Data Science & Machine Learning team in our Commercial Digital practice, 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.
What You’ll Do- 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.
- 2+ (3+ years for Sr. Associate) years of hands-on experience building and deploying ML solutions in production—not just notebooks and prototypes. You’ve trained models, put them into production, and maintained them.
- Strong Python and JavaScript programming skills with deep experience in the ML ecosystem (NumPy, Pandas, Scikit-learn, PyTorch or TensorFlow, etc.) and proficiency with JavaScript web app development.
- Solid foundation in ML fundamentals: supervised and unsupervised learning, model evaluation, feature engineering, hyperparameter tuning, and understanding of when different approaches are appropriate.
- Experience with cloud ML platforms, particularly Azure Machine Learning, with working knowledge of AWS SageMaker or Google AI Platform. We’re platform-flexible but Microsoft-preferred.
- Proficiency with data platforms: SQL, Snowflake, Databricks, or similar. You’re 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.
- Ability to communicate technical concepts to non-technical stakeholders and work effectively with cross-functional teams.
- Bachelor’s degree in Computer Science, Engineering, Mathematics, Physics, or related quantitative field (or equivalent practical experience).
- Flexibility to work in a hybrid model with periodic travel to client sites as needed.
- Experience in Financial Services, Manufacturing, or Energy & Utilities industries.
- Background in forecasting, optimization, or financial modeling applications.
- Experience with deep learning frameworks such as PyTorch, Tensorflow, fastai, DeepSpeed, etc.
- Experience with MLOps tools such as 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.
- Cloud certifications (Azure AI Engineer, AWS ML Specialty, or Databricks ML Associate).
- Consulting experience or demonstrated ability to work across multiple domains and adapt quickly to new problem spaces.
- Master’s degree or PhD in a quantitative field.
- Variety that accelerates your growth. In consulting, you’ll work across industries and problem types that would take a decade to encounter at a single company. Our Commercial segment spans Financial Services, Manufacturing, Energy & Utilities, and more—each engagement is a new domain to master and a new system to ship.
- Impact you can measure. Our clients are Fortune 500 companies making significant investments in AI. The models you build will inform real decisions—production schedules, pricing strategies, risk assessments, capital allocation. You’ll see your work drive outcomes.
- A team that builds. Huron’s Data Science & Machine Learning team is a close-knit group of practitioners, not just advisors. We write code, train models, and deploy systems. You’ll work alongside engineers and data scientists who understand the craft and push each other to improve.
- Investment in your development. We provide resources for continuous learning, conference attendance, and certification. As our DSML practice grows, there’s significant opportunity to take on technical leadership and shape our capabilities.
At Huron, we’re redefining what a consulting organization can be. We go beyond advice to deliver results that last. We inherit our client’s challenges as if they were our own. We help them transform for the future. We advocate. We make a difference. And we intelligently, passionately, relentlessly do great work…together. Whether you have years of experience or come right out of college, we invite you to explore our many opportunities. Find out how you can use your talents and develop your skills to make an impact immediately. Learn about how our culture and values provide you with the kind of environment that invites new ideas and innovation. Come see how we collaborate with each other in a culture of learning, coaching, diversity and inclusion. And hear about our unwavering commitment to make a difference in partnership with our clients, shareholders, communities and colleagues.
Huron Consulting Group offers a competitive compensation and benefits package including medical, dental, and vision coverage to employees and dependents; a 401(k) plan with a generous employer match; an employee stock purchase plan; a generous Paid Time Off policy; and paid parental leave and adoption assistance. Our Wellness Program supports employee total well-being by providing free annual health screenings and coaching, bank at work, and on-site.
Machine Learning Engineer in Belfast employer: Huron Consulting Group Inc.
Contact Detail:
Huron Consulting Group Inc. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer in Belfast
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects. Whether it's a GitHub repo or a personal website, having tangible examples of your work can really set you apart from the competition.
✨Tip Number 3
Prepare for interviews by brushing up on common ML concepts and frameworks. Practice explaining your past projects and how they relate to the role you're applying for. Confidence and clarity can make a huge difference!
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who are genuinely interested in joining our team. Plus, it makes it easier for us to track your application and get back to you quickly.
We think you need these skills to ace Machine Learning Engineer in Belfast
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Machine Learning Engineer role. Highlight relevant experience, especially in building and deploying ML solutions. We want to see how your skills align with what we do!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about machine learning and how you can contribute to our team. Be genuine and let your personality come through.
Showcase Your Projects: If you've worked on any cool ML projects, make sure to mention them! Whether it's a personal project or something from work, we love seeing practical applications of your skills. Include links if possible!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at Huron Consulting Group Inc.
✨Know Your ML Fundamentals
Brush up on your machine learning fundamentals, especially supervised and unsupervised learning, model evaluation, and feature engineering. Be ready to discuss how you've applied these concepts in real-world scenarios, as this will show your depth of understanding.
✨Showcase Your Projects
Prepare to talk about specific projects where you've designed and deployed ML solutions. Highlight the challenges you faced, the technologies you used (like Python, TensorFlow, or Azure), and the impact your work had on the business. This will demonstrate your hands-on experience.
✨Communicate Clearly
Practice explaining complex technical concepts in simple terms. You'll likely need to communicate with non-technical stakeholders, so being able to break down your work into digestible pieces is crucial. Think of examples where you've successfully done this before.
✨Understand the Company’s Needs
Research Huron and its focus areas, particularly in Financial Services, Manufacturing, and Energy & Utilities. Tailor your responses to show how your skills can directly address their needs and contribute to their projects. This shows you're not just interested in any job, but specifically in what they do.