AI Engineer - Build ML Infra for Trading

AI Engineer - Build ML Infra for Trading

Full-Time 60000 - 80000 Β£ / year (est.) No working from home possible
Oxford Knight

At a Glance

  • Tasks: Develop AI-driven infrastructure and collaborate with traders and data scientists.
  • Company: Join Oxford Knight, a leader in multi-asset trading innovation.
  • Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
  • Other info: Be part of a dynamic team with exciting challenges and career advancement.
  • Why this job: Make an impact by integrating advanced ML into real-world trading scenarios.
  • Qualifications: Strong Python skills and proficiency in machine learning are essential.

The predicted salary is between 60000 - 80000 Β£ per year.

Oxford Knight is seeking an AI Engineer to join a cutting-edge, multi-asset trading team.

You will develop AI-driven infrastructure and collaborate with traders, researchers, and data scientists to integrate advanced ML into business use cases.

You will lead automated training, validation, and monitoring, ensure reliable production models, and optimize compute resources across hardware environments.

Strong Python and ML proficiency are essential.

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AI Engineer - Build ML Infra for Trading employer: Oxford Knight

As one of the world's leading algorithmic trading firms, we offer an exceptional work environment where innovation thrives. Our friendly and informal culture fosters collaboration across teams, allowing you to tackle complex challenges with cutting-edge technologies while enjoying a market-leading salary and generous benefits. Join us to make a significant impact in the financial sector and advance your career in a role that values your contributions and expertise.

Oxford Knight

Contact Details:

Oxford Knight Recruitment Team

We think you need these skills to ace AI Engineer - Build ML Infra for Trading

Python
Machine Learning (ML)
AI-driven Infrastructure Development
Automated Training
Model Validation
Model Monitoring
Production Model Reliability