Our client, a leading hedge fund 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.
• Ability to bring thoughtful change through strong collaboration, values mindset, approach, and ownership - perceiving and addressing challenges through impactful ideas.