Join a world-class quantitative investment firm and shape the future of Machine Learning infrastructure as a Senior Data Engineer.
About the Role
This high-impact position combines data, infrastructure, and machine learning to support next-generation quantitative research and trading strategies. As a senior engineer, you will design and implement scalable, fault-tolerant data pipelines supporting ML workflows from feature engineering to model evaluation.
Key Responsibilities:
• Design and build internal platforms for model orchestration, experiment tracking, dataset versioning, and automated deployment of ML models.
• Partner with data scientists and quant researchers to deliver performant, reusable tooling and infrastructure.
• Oversee best practices in data engineering and ML Ops across ingestion, validation, transformation, and lineage tracking.
• Own monitoring, observability, and operational support for production data and ML pipelines.
Requirements
Extensive experience in Python (or Java/Scala) with strong system design and data engineering skills. Hands-on experience with modern ML Ops tooling such as Airflow or similar. Knowledge of containerization and orchestration in a production ML or data platform setting.
What We Offer
An opportunity to work at the intersection of data and machine learning, shaping the future of ML infrastructure within a world-class quantitative investment firm. Apply now for a confidential discussion.
