Our client is a highly regarded quantitative investment firm seeking a Research Engineer to join a growing technology team focused on enabling data-driven research. This position centres on developing Python-based tooling, data infrastructure, and workflow frameworks that allow researchers to efficiently work with large-scale financial and alternative datasets.

The ideal candidate will have experience building research platforms, orchestrating complex data workflows, and supporting machine learning research environments. A strong focus on data quality, MLOps, and GPU-enabled computing is essential.

Key Responsibilities

• Design, build, and maintain Python-based research tools and infrastructure.
• Develop scalable frameworks to support data analysis, feature generation, and research workflows.
• Curate and manage large, complex data-sets, ensuring high standards of quality, consistency, and accessibility.
• Enhance data pipelines for ingestion, validation, transformation, and distribution.
• Collaborate closely with research teams to translate requirements into robust engineering solutions.
• Support machine learning operations, including automation, experiment tracking, and reproducibility.
• Optimise GPU-enabled environments to improve research efficiency and performance.
• Work alongside platform and infrastructure teams to ensure systems are scalable, reliable, and well-governed.

Required Experience

• Strong software engineering background with Python as a core development language.
• Experience building research platforms, data infrastructure, or data-intensive applications.
• Proven experience working with large-scale data-sets in a research, quantitative, or analytical environment.
• Strong understanding of data management, governance, and quality control.
• Experience designing and supporting orchestration frameworks and large-scale data processing workflows.
• Familiarity with MLOps principles, tooling, and best practices.
• Experience supporting GPU-based workloads for machine learning or research applications.
• Excellent problem-solving skills and strong attention to detail.
• Ability to work effectively with researchers, data scientists, and engineering teams.