Our client, a prestigious financial institution, is renowned for its expertise in quantitative trading, is looking to hire a talented Machine Learning Engineer.
With decades of experience and a data-driven approach, the firm applies advanced machine learning and statistical analysis to inform asset allocation, trading strategies, and automated execution. Regulated across multiple jurisdictions, it maintains a strong foundation in research, technology, and disciplined processes.
You would be joining the Machine Learning Platform team, a high-impact team tackling major technical challenges in a transformative machine learning environment. The role focuses on evolving machine learning practices toward direct, production-level applications - acting as a catalyst for innovation within the firm. You'll work on creating value through mathematical algorithms in a stimulating, hands-on culture that bridges research and real-world execution.
Key Responsibilities:
- Drive the adoption and effective use of internal machine learning tools and services.
- Collaborate with users to evolve the ML platform in line with real-world needs.
- Define and implement best practices for ML development, ensuring reproducibility, quality, and auditability.
- Develop self-service solutions to streamline and accelerate ML workflows.
- Support and mentor junior engineers as the team grows.
- Deliver training and promote high standards in ML-related software development across the organization.
Requirements:
- 5+ years of hands-on experience in putting Machine Learning solutions into production and handling MLOps challenges.
- Good knowledge in ML and deep learning tools such as TensorFlow and/or Pytorch, MLFlow or similar platforms, and interference servers like Triton.
- Good knowledge in Python is essential.
- Familiarity with containerization technologies and UNIX-based systems is important.
- Knowledge in AWS is required.
Key Skills
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- Posted
- Oct 17, 2025
- Type
- Full-time
- Level
- Mid-Senior
- Location
- Paris
- Company
- Selby Jennings
Industries
Categories
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