AI Engineer - Job Specification
Location : Belfast
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: Minimum 5 years 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
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