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Data Science, AI & Machine Learning Consultant at La Fosse

Machine Learning Engineer

• London (Hybrid)
• Up to 65,000

One of La Fosses best clients are currently seeking a talented ML Engineer for their greenfield AI team. Join a cutting-edge innovation department within a fast-paced financial environment, helping to shape the next generation of intelligent compliance tools.

Im looking for a Machine Learning Engineer to join a small & agile development team focused on building out a greenfield AI-powered transaction monitoring platform. You'll work on everything from ML model development and GenAI summarisation pipelines to MLOps and multi-agent systemswith real-world impact on financial security and compliance.

What Youll Do:

• Develop and deploy machine learning models for anti-money laundering and counter-terrorist financing.
• Contribute to dynamic monitoring systems using tools like TensorFlow, OpenAI, and LangChain.
• Help design GenAI pipelines and consensus mechanisms across a distributed agent system.
• Work alongside DevOps to build scalable, automated ML deployment pipelines.
• Write clean, well-documented code using Python and modern tooling (gRPC, Alembic, Pytest, etc.).

Requirements:

• 13 years of experience in ML or AI
• Proficiency in Python, SQL, cloud platforms (Azure), and modern ML frameworks (TensorFlow, PyTorch).
• Familiarity with generative AI, deep learning, and the full development lifecycle.
• A proactive mindset and strong interest in innovative technologies.

Why Join?

• Be part of a greenfield AI initiative with high visibility
• Work in a fast-moving, collaborative environment
• Help shape a platform being considered for national-level compliance adoption
• Growth opportunities in a company that values curiosity and initiative

If youre interested in finding out more, apply through the AD with your CV!

Machine Learning Engineer

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Information Technology, Finance, and Engineering

• Industries

  Data Infrastructure and Analytics, Information Services, and Financial Services

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