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AI / ML Engineer

AI / ML Engineer

Quality Control Specialist - Pest ControlLondon, England, United Kingdom
11 days ago
Job type
  • Full-time
Job description

You'll work at the intersection of artificial intelligence, quantitative research, and alpha generation, building advanced systems that support high-impact decision-making across discretionary and systematic strategies.

This is a hands-on role for someone passionate about building AI tools in a real-world, fast-paced environment. While finance industry experience is preferred, the team is also open to candidates from elite engineering backgrounds (e.g. top-tier product / AI companies) who can demonstrate strong technical depth and delivery in applied AI.

What You'll Be Doing

  • Design and develop AI / ML solutions to enhance investment decision-making and automate analyst workflows.
  • Build tools that improve semantic search, NLP, knowledge extraction, and internal research capabilities.
  • Collaborate with portfolio managers, researchers, and data engineers to translate business problems into ML use cases.
  • Implement, evaluate, and optimize LLM-based solutions, leveraging vector databases and retrieval-augmented generation (RAG) techniques.
  • Stay current with developments in GenAI, open-source models, and novel ML frameworks, contributing to innovation across the firm.
  • Deploy models across hybrid cloud environments (on-prem and AWS), and work with tools like Kafka, Spark, and cloud-native data warehouses.

What We're Looking For

  • 3+ years' experience in AI / ML engineering, ideally with applied work in real-time or data-intensive environments.
  • Strong programming skills in Python.
  • Experience with AI / ML frameworks such as PyTorch, TensorFlow, scikit-learn, or similar.
  • Familiarity with LLM stacks and GenAI tools (e.g. LangChain, LlamaIndex, OpenAI API).
  • Knowledge of vector databases, graph-based systems, and unstructured data processing is a plus.
  • Background in building and scaling infrastructure in cloud environments (AWS preferred).
  • Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related quantitative field.
  • Experience working with hedge funds, trading firms, or financial data.
  • Exposure to quantitative research, signal generation, or alpha discovery workflows.
  • Understanding of secure data governance, model evaluation, and production ML operations in regulated environments.

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