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Senior Research Engineer - Selby Jennings

External
eFinancialCareers logoEfinancialcareers · London, UK
Full-timeOn-site1d ago
AccessibilityData AnalysisMachine LearningMLOpsPython
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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.

Additional Information

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.


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