Senior Engineer, Systematic Research Technology

We are seeking a Senior Research Engineer to join our Systematic Technology team. This role will focus on building Python-based research tooling and infrastructure that enables quantitative researchers to work efficiently with large financial and alternative datasets .

The ideal candidate will have strong experience in data curation , research orchestration , and scalable data processing, along with a high level of attention to detail . Experience with MLOps and optimizing GPU usage for research workloads is also important.

• Build and maintain research tooling and infrastructure in Python .
• Develop orchestration frameworks for large-scale data analysis, feature generation, and research workflows.
• Curate and manage broad financial and alternative datasets, with strong focus on quality, consistency, and usability .
• Improve data pipelines for ingestion, validation, transformation, and distribution.
• Partner with Quantitative Researchers to translate research needs into scalable engineering solutions.
• Support MLOps workflows, including automation, experiment management, and reproducibility.
• Optimize GPU integration and utilization across research workloads.
• Work with platform and infrastructure teams to ensure research systems are scalable, reliable, and efficient.

• Strong software engineering skills with Python as a primary language .
• Experience building research tooling, data infrastructure, or data-intensive platforms .
• Strong experience working with large financial and/or alternative datasets .
• Expertise in data curation and maintaining high standards of data quality.
• Experience with research orchestration and large-scale data processing workflows.
• Familiarity with MLOps practices and tooling.
• Experience supporting or optimizing GPU-based research or machine learning workloads.
• Strong attention to detail and ability to work closely with Quantitative Researchers.

• Experience in systematic investing or quantitative research environments.
• Familiarity with alternative data workflows and large-scale analytical platforms.
• Experience with distributed compute, workflow orchestration, and reproducible research environments.
• Exposure to cloud, containerization, or shared compute infrastructure.

Success in the Role

Success in this role will require:

• Strong Python engineering skills
• Excellent data quality and attention to detail
• The ability to support research at scale across large datasets
• Strong partnership with researchers
• Practical experience with MLOps and GPU optimization