Senior Consultant / AI Engineer / AI & Data UKI

Ernst & Young GmbH Wirtschaftsprüfungsgesellschaft; Greater London; On-site; GBP 60,000 - GBP 80,000; Full time

Job summary

A global professional services firm in London is seeking an AI Engineer to develop and deploy machine learning and AI solutions. The role requires expertise in building LLMs for diverse applications and collaborating with cross-functional teams. Candidates should have a degree in a quantitative field and demonstrate hands-on experience with tools like Databricks, Azure ML, or Snowflake. This position offers opportunities for growth in a supportive environment focused on shaping a better working world.

Benefits

Competitive salary

Professional development opportunities

Contribution to impactful projects

Qualifications

• Hands-on experience developing machine learning models and AI solutions.
• Proven experience with LLM-based solutions like GPT or Claude.
• Strong analytical mindset with attention to detail.

Responsibilities

• Develop and deploy end-to-end machine learning models.
• Collaborate with engineers and analysts on integrated solutions.
• Translate business requirements into technical features.

Skills

Machine learning

Natural language processing

Python programming

Data analysis

Consulting skills

Education

Degree in Computer Science or related field

Tools

Databricks

Azure Machine Learning

Snowflake

Job description

Overview

Location: London

Other locations: Primary Location Only

Requisition ID: 1654443

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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 and automation pathways across diverse use cases including finance forecasting, energy optimization, predictive maintenance, supply chain planning, and commercial transformation, leveraging modern cloud-based AI platforms.

• 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
• 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
• Proven experience building and implementing LLM-based solutions (GPT, Claude, Llama, Mistral, or similar)
• Hands-on 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 (scikit-learn, pandas, NumPy, XGBoost, LightGBM)
• 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
• Consulting skills, supporting development of presentation decks and communication

Preferred 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, 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
• 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 optimization, logistics planning, procurement analytics
• Commercial Transformation: Price optimization, customer lifetime value, churn prediction, marketing mix modelling

Preferred Qualifications

• Certifications such as:
• Azure AI Engineer Associate or Data Scientist Associate

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