Generative AI Engineer

This role is with a well-known leading global financial institution operating across investment banking, asset management, and financial services. Renowned for its scale and innovation, it leverages advanced technology and AI to drive efficiency, security, and growth worldwide. We are seeking a highly skilled and motivated AI Engineer to join a cutting-edge team building intelligent autonomous agents for real-world deployment within complex systems. This role is ideal for individuals passionate about the future of AI, autonomous systems, and large-scale applications in a high-impact industry.

Core Details:

• Pay Rate: Circa £1000 p/d via PAYE Model (Flexible on rate)
• Location: Central London (or Glasgow) – 5 Days a Week On-site (No Flexibility)
• Length: 6 – 12 Months – with sight to go perm if preferred
• Financial Services Background is NOT NECESSARY - we are open to candidates of all backgrounds (tech native organisations are desirable)

Job Responsibilities:

• Act as a subject matter expert in a broad range of machine learning (ML) techniques and optimisations.
• Provide deep technical knowledge of ML algorithms, frameworks, and methodologies.
• Improve ML workflows through advanced skills in large language models (LLMs) and associated techniques.
• Design and run experiments using the latest ML technologies; analyse results and fine-tune models.
• Write production-level code in Python, transforming experimental outcomes into real-world applications by closely collaborating with engineering teams.
• Take ownership of end-to-end development for both proof-of-concept work and production-ready solutions.
• Improve system accuracy and efficiency by identifying performance issues and removing bottlenecks.
• Partner with product and engineering teams to create bespoke, technology-driven solutions.
• Integrate Generative AI techniques into the ML platform using cutting-edge methods.

Required Qualifications, Capabilities, and Skills:

• Formal academic training or certification (Master’s or PhD) in Computer Science, Machine Learning, or a related discipline, with hands-on experience in applied ML.
• Proficiency in at least one programming language such as Python, Java, or C/C++. Intermediate-level Python is essential.
• Proven experience applying data science and ML techniques to practical business challenges.
• Strong background in Natural Language Processing (NLP) and working with Large Language Models (LLMs).
• Practical experience with both machine learning and deep learning techniques.
• Expert-level knowledge of deep learning frameworks like PyTorch or TensorFlow.
• Experience in advanced ML areas including GPU optimisation, fine-tuning, embedding models, inference, prompt engineering, evaluation, and Retrieval-Augmented Generation (RAG).
• Ability to independently manage and complete tasks and projects with minimal supervision.
• High attention to detail, strong follow-through, excellent communication abilities, and a collaborative mindset.

Preferred Qualifications, Capabilities, and Skills:

• Master’s degree in Computer Science, Machine Learning, or a related field.
• Experience with distributed training frameworks such as Ray, MLFlow, or similar.
• Deep understanding of advanced ML techniques, including search and ranking, recommender systems, and graph-based methods.
• Expertise in LLM-based approaches, including Agents, Planning, and Reasoning.
• Familiarity with deploying ML models on cloud platforms like AWS, including tools such as SageMaker and EKS.
• Experience working with large-scale MLOps pipelines and deploying models into production environments.