AI/ML and Data Science Developer

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 (phone number removed) and ask for Ben