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AI Engineer - Job Specification
Location : London
Position Overview
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. This role requires hands-on experience building AI models across diverse use cases including finance forecasting, energy optimization, predictive maintenance, supply chain planning, and commercial transformation, leveraging modern cloud-based AI platforms.
Your client impact
Design, develop, and deploy end-to-end machine learning models for complex business problems across forecasting, optimization, and prediction domains
Build and fine-tune 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
Translate business requirements into technical AI/ML features, model selection, architecture decisions
Conduct exploratory data analysis and communicate insights to stakeholders
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
Required Qualifications
Essential: Strong level of hands-on experience developing and deploying machine learning models in production environments
Essential: Proven experience building and implementing LLM-based solutions (GPT, Claude, Llama, Mistral, or similar)
Deep understanding of machine learning algorithms including supervised, unsupervised, and reinforcement learning approaches
Strong proficiency in statistical modeling, time-series forecasting, and predictive analytics
Experience with deep learning frameworks (TensorFlow, PyTorch, Keras)
Knowledge of prompt engineering, RAG (Retrieval Augmented Generation), and LLM fine-tuning techniques
Understanding of natural language processing, computer vision, and recommender systems Essential: Hands-on experience with at least one of: Databricks (MLflow, AutoML), Azure Machine Learning, or Snowflake (Snowpark ML, Cortex)
Strong programming skills in Python and proficiency with ML libraries (scikit-learn, pandas, NumPy, XGBoost, LightGBM)
Familiarity with distributed computing frameworks (Spark, Dask, Ray)
Strong analytical and problem-solving mindset with attention to detail
Ability to work independently and drive projects from ambiguous requirements
Story telling with data and insights from the outputs
Preferred Experience
Finance Forecasting: Revenue prediction, cashflow modeling, financial planning, risk modeling
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 optimization, logistics planning, procurement analytics
Commercial Transformation: Price optimization, customer lifetime value, churn prediction, marketing mix modeling
Preferred Qualifications
Advanced degree (Master's or PhD) in Computer Science, Data Science, Statistics, Mathematics, Engineering, or related quantitative field
Big 4 or tier-1 consulting firm experience
Certifications such as: Databricks Certified Machine Learning Professional
Azure AI Engineer Associate or Data Scientist Associate
SnowPro Advanced: Data Scientist
AWS Certified Machine Learning - Specialty Experience with generative AI platforms (Azure OpenAI, AWS Bedrock, Vertex AI)
Knowledge of graph neural networks, reinforcement learning, or causal inference
Experience with AI governance, model risk management, and regulatory compliance
EY | Building a better working world
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, multi-disciplinary network and diverse ecosystem partners, EY teams can provide services in more than 150 countries and territories.
