Artificial Intelligence Engineer

As an AI Engineer at this award-winning quantitative hedge fund in London, you will be an integral member of a collaborative team. You’ll work on high-impact machine learning and artificial intelligence projects that are central to the firm's strategy. In this role, you will build critical infrastructure and tooling that leverages AI and ML technology to enhance productivity, efficiency, and discover innovative paths to challenging business and technology problems. Surrounded by cutting-edge technology and experienced trading teams, you will have the opportunity to tackle fascinating new projects.

Responsibilities:

• End-to-end development of AI infrastructure and AI-driven applications: from initial proof-of-concept to production deployment and ongoing maintenance.
• Collaborate with technologists, traders, and quantitative researchers to identify high-impact opportunities for integrating AI and machine learning into technology and business use cases.
• Implement automated systems for continuous training, validation, and monitoring of models, minimising downtime and ensuring reliability.
• Provide technical leadership in selecting, integrating, and optimising AI and ML frameworks, libraries, and tools across diverse hardware and software environments.
• Create and maintain feature pipelines, feature stores, and model stores.
• Develop frameworks to enable scalable, reproducible research.
• Proactively troubleshoot performance bottlenecks, conduct root-cause analyses, and implement solutions to optimise GPU or CPU resource usage.

Qualifications:

• 5+ years of experience working with machine learning and artificial intelligence technology. Strong understanding of core machine learning and artificial intelligence concepts.
• Excellent programming skills in Python.
• Demonstrated experience in building, validating, deploying, monitoring, and updating production ML and AI models.
• Hands-on experience with MLOps and AIOps infrastructure and tooling.
• Proficient in problem-solving and analytical reasoning.
• Exceptional communication and collaboration skills.
• Experience with ML frameworks such as TensorFlow, PyTorch, TensorRT, or ONNX.
• Experience with Large Language Models, including RAG and fine-tuning techniques.
• Familiarity with computing infrastructure necessary to support operating AI and ML technology.
• Experience in financial markets trading at either an elite hedge fund, prop trading firm or specialist liquidity provider.