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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.