AI - ML Engineer

We're looking for a Senior AI/ML Engineer to help design, develop, and scale intelligent systems that solve real-world challenges using the latest in machine learning, NLP, and computer vision. In this role, you'll be responsible for turning complex business problems into data-driven solutions-owning the entire ML lifecycle from data wrangling and model development to deployment and continuous optimisation in production.

You'll work closely with product, engineering, and data teams to integrate AI solutions into high-impact systems, while mentoring junior team members and contributing to a culture of experimentation, innovation, and engineering excellence.

What you'll do:

• Develop, train, and deploy scalable ML models that power production-grade systems

• Apply advanced techniques across LLMs, NLP, and/or computer vision to solve complex use cases

• Conduct rigorous data analysis and feature engineering to optimise training datasets

• Continuously tune model performance and scalability using the latest research and tooling

• Stay on the cutting edge of AI advancements, applying new methods where they create value

• Collaborate cross-functionally to embed models into real-world applications and services

• Guide junior engineers and contribute to shared knowledge through code reviews and mentoring

• Communicate technical insights clearly to both technical and non-technical audiences

• Contribute to best practices around MLOps, version control, testing, and continuous delivery

What you bring:

• 2+ years of hands-on experience in machine learning or AI (10+ years total in tech or engineering)

• Strong Python skills (R also welcome), with experience using ML libraries like TensorFlow, PyTorch, and Scikit-learn

• Exposure to LLMs, NLP, or computer vision in practical environments

• Deep understanding of algorithms, statistics, and data structures

• Proven success deploying models in production at scale

• Experience working in cloud environments such as AWS, GCP, or Azure

• Familiarity with big data tools (e.g., Spark, Kafka) and DevOps/CI-CD practices

• A degree in Computer Science, Engineering, Mathematics, or a related field