AI/ML and Data Science Developer - Harrington Boyd : Job Details

AI/ML and Data Science Developer

Hybrid - Stevenage 3/4dpw

£70,000 - £80,000

About the Role:

We are looking for an AI/ML and Data Science Developer to join a growing team working on cutting-edge Generative AI and Data Science solutions. This role offers the opportunity to design, develop, and deploy advanced AI/Machine Learning models, including Large Language Models (LLMs) and GenAI, while working with diverse datasets and modern deployment technologies.

You'll play a key role in data processing, model fine-tuning, and deployment, helping to shape innovative solutions that make a tangible impact.

Key Responsibilities:

• Design, develop, and deploy AI/Machine learning models and solutions, including LLMs and GenAI.
• Fine-tune and evaluate open-source LLMs, applying techniques such as prompt engineering and model re-tuning.
• Work with a variety of structured and unstructured datasets, handling preprocessing, cleaning, and feature engineering.
• Develop pipelines for creating, preparing, and optimising data for modelling.
• Deploy models to production using containerisation tools (Docker, Kubernetes) and ensure scalability, robustness, and monitoring.
• Research and apply the latest advancements in Generative AI and data science.
• Support model evaluation, logging, and performance tuning across GPU-based environments.
• Collaborate with stakeholders to gather requirements and deliver solutions aligned to business needs.
• Document workflows, data pipelines, and model processes for knowledge transfer and reproducibility.

Key Skills & Experience:

• 4-5 years' experience across AI/ML, data science, or data engineering, with recent hands-on work in GenAI.
• Proven experience fine-tuning and deploying open-source LLMs.
• Strong knowledge of AI/ML algorithms and techniques (supervised, unsupervised, reinforcement learning).
• Solid background in data preprocessing, wrangling, and feature engineering.
• Proficiency in Python (essential) and familiarity with relevant libraries (NumPy, pandas, scikit-learn, TensorFlow, PyTorch).
• Experience with prompt engineering and model evaluation.
• Deployment experience using Docker or other containerisation tools.
• Exposure to GPU-based environments for large-scale model training and tuning.
• Experience with big data tools (Spark, Hadoop) and cloud platforms (AWS, GCP, Azure) is a plus.
• Strong analytical mindset with the ability to translate data into actionable insights.

If you or someone you know of might be interested, please contact and ask for Ben.