Senior Research Engineer

Quick Facts

Role: Senior Research Engineer (Systematic Technology)

Focus: Python research tooling, data infrastructure, orchestration, MLOps, and GPU/compute optimization

Description

You will design, build, and optimize Python-based research tooling and data infrastructure that enables quantitative researchers to iterate quickly and scale analysis of massive financial and alternative datasets.

Responsibilities

• Build and scale core Python frameworks and internal libraries used by quantitative researchers
• Develop orchestration systems and workflow pipelines for large-scale data analysis and automated feature generation
• Curate and manage financial and alternative datasets with strong data quality, consistency, point-in-time accuracy, and usability standards
• Improve ingestion, validation, transformation, and distribution pipelines for zero-data-loss and low-latency delivery
• Collaborate with quantitative researchers to translate research models into production-grade engineering solutions
• Support MLOps workflows, including experiment reproducibility, automated pipeline tracking, and model management
• Optimize GPU resource allocation and utilization for compute-heavy and parallelized machine learning jobs
• Partner with platform/infrastructure teams to ensure scalability, high availability, and system efficiency

Requirements

• Excellent software engineering foundation in modern Python (clean code, modular design, performance tuning)
• Direct experience building data-intensive platforms, research tooling, or large-scale data pipelines
• Hands-on experience working with large-scale financial markets data, alt-data, or high-throughput tabular time-series
• Uncompromising attention to data quality and rigorous data validation, cleansing, and curation practices
• Proven experience with data orchestration frameworks and large-scale analytical processing
• Practical familiarity with MLOps concepts (experiment tracking, pipeline automation)
• Experience supporting or accelerating GPU-based research workloads or machine learning infrastructure

Benefits

No benefits were provided in the source posting.