At a Glance
- Tasks: Develop and deploy advanced AI solutions that drive real business impact.
- Company: Join EY, a global leader in professional services with a diverse team culture.
- Benefits: Enjoy competitive salary, health benefits, and opportunities for remote work.
- Why this job: Make a difference by solving complex problems with cutting-edge AI technology.
- Qualifications: Experience in AI/ML solutions and strong programming skills required.
- Other info: Dynamic environment with excellent career growth and learning opportunities.
The predicted salary is between 43200 - 72000 £ per year.
We are seeking a highly skilled AI Engineer with proven expertise in developing and deploying advanced machine learning and large language model (LLM) solutions that drive measurable business impact.
Your client impact:
- Develop and deploy endātoāend machine learning models for complex business problems across forecasting, optimization, and prediction domains.
- Build and fineātune large language models (LLMs) for enterprise applications including document intelligence, conversational AI, and decision support systems.
- Deep understanding of solving data science and AI enabled problems in supply chain, finance, commercial or operations domain or AI agents with reasoning capabilities using LLMs.
- Adapt to a wide range of technical challenges across technologies to design a solution applicable to the business issue.
- Translate business requirements into technical AI/ML features, model selection, architecture decisions.
- Conduct exploratory data analysis and communicate insights.
- Collaborate with data engineers, architects, and business analysts on integrated solutions.
- Build feature engineering pipelines and automated data preparation workflows.
- Design AI solutions for commercial transformation including pricing optimization, customer segmentation, and revenue management.
- Develop scalable AI/ML pipelines on Databricks, Azure Machine Learning, and/or Snowflake platforms.
- Contribute to proposals and technical assessments for new opportunities and internal knowledge transfer.
Essential Qualifications:
- Degree or equivalent certification in Computer Science, Data Science, Statistics, Mathematics, Engineering, or related quantitative field.
Essential Criteria:
- Proven experience building and implementing LLM-based solutions (GPT, Claude, Llama, Mistral, or similar).
- Handsāon experience with at least one of: Databricks (MLflow, AutoML), Azure Machine Learning, or Snowflake (Snowpark ML, Cortex).
- Understanding of natural language processing, computer vision, and recommender systems.
- Strong programming skills in Python, SQL and proficiency with ML libraries (scikitālearn, pandas, NumPy, XGBoost, LightGBM).
Soft Skills:
- Strong analytical and problemāsolving mindset with attention to detail.
- Ability to work independently and drive projects from ambiguous requirements.
- Storytelling with data and insights from the outputs.
- Consulting skills, supporting development of presentation decks and communication.
Desired Criteria:
- Experience or knowledge covering at least one of the following areas:
- Deep understanding of machine learning algorithms including supervised, unsupervised, and reinforcement learning approaches.
- Strong proficiency in statistical modelling, timeāseries forecasting, and predictive analytics.
- Experience with deep learning frameworks (TensorFlow, PyTorch, Keras).
- Knowledge of prompt engineering, RAG (Retrieval Augmented Generation), and LLM fineātuning techniques.
- Familiarity with distributed computing frameworks (eg Spark).
- Knowledge of graph neural networks, reinforcement learning, or causal inference.
- Experience with AI governance, model risk management, and regulatory compliance.
- Experience using Pro code and Low code tools such as LangGraph, AutoGen, Semantic Kernal and MS CoPilot.
- Experience in any of the following:
- Finance Forecasting: Revenue prediction, cashflow modelling, financial planning, risk modelling.
- Energy Optimization: Load forecasting, grid optimization, demand response, renewable energy prediction.
- Predictive Maintenance: Equipment failure prediction, anomaly detection, remaining useful life estimation.
- Supply Chain Planning: Demand forecasting, inventory optimisation, logistics planning, procurement analytics.
- Commercial Transformation: Price optimisation, customer lifetime value, churn prediction, marketing mix modelling.
Preferred Qualifications:
- Certifications such as:
- Databricks Certified Machine Learning Professional.
- Azure AI Engineer Associate or Data Scientist Associate.
- SnowPro Advanced: Data Scientist.
- AWS Certified Machine Learning ā Specialty.
EY is building a better working world by creating new value for clients, people, society and the planet, while building trust in capital markets. Enabled by data, AI and advanced technology, EY teams help clients shape the future with confidence and develop answers for the most pressing issues of today and tomorrow. EY teams work across a full spectrum of services in assurance, consulting, tax, strategy and transactions. Fueled by sector insights, a globally connected, multiādisciplinary network and diverse ecosystem partners, EY teams can provide services in more than 150 countries and territories.
Seniority level: MidāSenior level
Employment type: Fullātime
Job function: Consulting, Information Technology, and Sales
Industries: Professional Services
(INV) Senior Consultant, AI Engineer, AI&Data, UKI Northern Ireland in Belfast employer: EY
Contact Detail:
EY Recruiting Team
StudySmarter Expert Advice š¤«
We think this is how you could land (INV) Senior Consultant, AI Engineer, AI&Data, UKI Northern Ireland in Belfast
āØTip Number 1
Network like a pro! Reach out to current employees at EY through LinkedIn or other platforms. Ask them about their experiences and any tips they might have for landing the Senior Consultant role. Personal connections can make a huge difference!
āØTip Number 2
Prepare for those interviews! Brush up on your technical skills, especially around machine learning and AI solutions. Be ready to discuss your past projects and how they relate to the job description. Practice makes perfect!
āØTip Number 3
Showcase your problem-solving skills! During interviews, highlight specific examples where you've tackled complex business problems using AI. This will demonstrate your ability to drive measurable impact, which is key for this role.
āØTip Number 4
Donāt forget to apply through our website! Itās the best way to ensure your application gets seen by the right people. Plus, it shows youāre serious about joining the EY team and building a better working world together.
We think you need these skills to ace (INV) Senior Consultant, AI Engineer, AI&Data, UKI Northern Ireland in Belfast
Some tips for your application š«”
Tailor Your CV: Make sure your CV is tailored to the role of Senior Consultant, AI Engineer. Highlight your experience with machine learning and LLMs, and donāt forget to mention any relevant projects that showcase your skills!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to tell us why youāre passionate about AI and how your background makes you a perfect fit for our team. Be specific about what excites you about the role.
Showcase Your Technical Skills: We want to see your technical prowess! Include specific examples of your work with Databricks, Azure Machine Learning, or Snowflake. Mention any programming languages and ML libraries youāre proficient in, like Python and scikit-learn.
Apply Through Our Website: Donāt forget to apply through our website! Itās the best way to ensure your application gets into the right hands. Plus, it shows us youāre serious about joining our team at EY.
How to prepare for a job interview at EY
āØKnow Your AI Models Inside Out
Make sure youāre well-versed in the latest large language models (LLMs) like GPT and Claude. Be ready to discuss your hands-on experience with these technologies, as well as how you've applied them to solve real business problems.
āØShowcase Your Technical Skills
Prepare to demonstrate your programming prowess in Python and SQL. Brush up on your knowledge of ML libraries like scikit-learn and TensorFlow, and be ready to explain how you've used them in past projects.
āØCommunicate Clearly and Effectively
Practice storytelling with data. Youāll need to convey complex insights in a way thatās easy to understand. Think about examples where youāve turned data analysis into actionable business strategies.
āØCollaborate and Adapt
Highlight your experience working with cross-functional teams. Be prepared to discuss how youāve collaborated with data engineers and business analysts to create integrated solutions, and show your adaptability to various technical challenges.