Machine Learning Engineer

A premier Global Hedge Fund and quantitative investment firm, recognized for its technological leadership in the financial markets. The firm develops high-performance systems for real-time pricing, risk management, and market analysis. Operating at the intersection of finance and cutting-edge R&D, the organization offers a highly competitive environment and industry-leading conditions for top-tier technical talent.

Located in the Central District (ideally situated near the train station), the firm operates a fully in-office model to support seamless collaboration with global teams.

Role Overview:

• Joining a Global ML & Data Science group as the primary local technical authority in the field.
• Reporting to a Group Lead in New York, while collaborating with local leadership and international R&D hubs.
• The role is a strategic hybrid of 60% AI Research (specializing in NLP and LLMs) and 40% ML Infrastructure & Engineering.
• Developing end-to-end AI/ML solutions across Cloud (AWS/GCP) and On-premise environments.
• Designing and implementing scalable pipelines using Python, Airflow, MLflow, and MLOps frameworks.
• Utilizing TensorFlow, PyTorch, and SageMaker to drive innovation and optimization in trading processes.

Requirements:

• B.Sc. in Exact Sciences (Mathematics, Computer Science, or related) from a leading university – Mandatory.
• 3+ years of professional experience in roles such as ML Engineer, Data Scientist, or AI Engineer – Mandatory.
• Deep hands-on proficiency in Python (candidates will undergo rigorous technical testing) – Mandatory.
• Proven experience working in Cloud environments (AWS or GCP) – Mandatory.
• Strong background in NLP and LLM implementation or research – Mandatory.
• Experience with MLOps tools and framework orchestration (e.g., MLflow, SageMaker, Airflow).
• M.Sc. in a quantitative or scientific field – A significant advantage.