Senior Consultant, AI Engineer, AI&Data, UKI
Role details
Job location
Tech stack
Job description
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
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Design, develop, and deploy end-to-end machine learning models for complex business problems across forecasting, optimization, and prediction domains
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Build and fine-tune large language models (LLMs) for enterprise applications including document intelligence, conversational AI, and decision support systems
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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
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Translate business requirements into technical AI/ML features, model selection, architecture decisions
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Conduct exploratory data analysis and communicate insights to stakeholders
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Collaborate with data engineers, architects, and business analysts on integrated solutions
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Build feature engineering pipelines and automated data preparation workflows
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Design AI solutions for commercial transformation including pricing optimization, customer segmentation, and revenue management
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Develop scalable AI/ML pipelines on Databricks, Azure Machine Learning, and/or Snowflake platforms
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Contribute to proposals and technical assessments for new opportunities
Requirements
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Essential: Strong level of hands-on experience developing and deploying machine learning models in production environments
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Essential: Proven experience building and implementing LLM-based solutions (GPT, Claude, Llama, Mistral, or similar)
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Deep understanding of machine learning algorithms including supervised, unsupervised, and reinforcement learning approaches
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Strong proficiency in statistical modeling, time-series forecasting, and predictive analytics
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Experience with deep learning frameworks (TensorFlow, PyTorch, Keras)
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Knowledge of prompt engineering, RAG (Retrieval Augmented Generation), and LLM fine-tuning techniques
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Understanding of natural language processing, computer vision, and recommender systems
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Essential: Hands-on experience with at least one of: Databricks (MLflow, AutoML), Azure Machine Learning, or Snowflake (Snowpark ML, Cortex)
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Strong programming skills in Python and proficiency with ML libraries (scikit-learn, pandas, NumPy, XGBoost, LightGBM)
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Familiarity with distributed computing frameworks (Spark, Dask, Ray)
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Strong analytical and problem-solving mindset with attention to detail
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Ability to work independently and drive projects from ambiguous requirements
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Story telling with data and insights from the outputs
Preferred Experience
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Finance Forecasting: Revenue prediction, cashflow modeling, financial planning, risk modeling
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Energy Optimization: Load forecasting, grid optimization, demand response, renewable energy prediction
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Predictive Maintenance: Equipment failure prediction, anomaly detection, remaining useful life estimation
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Supply Chain Planning: Demand forecasting, inventory optimization, logistics planning, procurement analytics
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Commercial Transformation: Price optimization, customer lifetime value, churn prediction, marketing mix modeling, * Advanced degree (Master's or PhD) in Computer Science, Data Science, Statistics, Mathematics, Engineering, or related quantitative field
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Big 4 or tier-1 consulting firm experience
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Certifications such as:
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Databricks Certified Machine Learning Professional
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Azure AI Engineer Associate or Data Scientist Associate
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SnowPro Advanced: Data Scientist
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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