Machine Learning Systems Engineer: Data

Overview

We’re looking for a Machine Learning Systems Engineer to help build the data infrastructure that powers our ML research. In this role, you'll develop reliable, high-performance systems for handling large and complex datasets, with a focus on scalability and reproducibility. You’ll partner with researchers to support experimental workflows and help translate evolving needs into efficient, production-ready solutions. The work involves optimizing compute performance across distributed systems and building low-latency, high-throughput data services. This role is ideal for someone with strong engineering instincts, a deep understanding of data systems, and an interest in supporting innovative machine learning efforts.

Why Join Us?

Susquehanna is a global quantitative trading firm that combines deep research, cutting-edge technology, and a collaborative culture. We build most of our systems from the ground up, and innovation is at the core of everything we do. As a Machine Learning Systems Engineer, you’ll play a critical role in enabling research at scale, accelerating experimentation, and helping unlock new opportunities across the firm.

What You’ll Do

• Design and implement high-performance data pipelines for processing large-scale datasets with an emphasis on reliability and reproducibility
• Collaborate with researchers to translate their requirements into scalable, production-grade systems for ML experimentation
• Optimize resource utilization across our distributed computing infrastructure through profiling, benchmarking, and systems-level improvements
• Implement low-latency high-throughput sampling for models

What we’re looking for

• Experience building and maintaining data pipelines and ETL systems at scale
• Experience with large-scale ML infrastructure and familiarity with training and inference workflows
• Strong understanding of best practices in data management and processing
• Knowledge of systems level programming and performance optimization
• Proficiency in Python
• Understanding of machine learning workloads, including data preprocessing, feature engineering, and model evaluation

About Susquehanna

Susquehanna is a global quantitative trading firm powered by scientific rigor, curiosity, and innovation. Our culture is intellectually driven and highly collaborative, bringing together researchers, engineers, and traders to design and deploy impactful strategies in our systematic trading environment. To meet the unique challenges of global markets, Susquehanna applies machine learning and advanced quantitative research to vast datasets in order to uncover actionable insights and build effective strategies. By uniting deep market expertise with cutting-edge technology, we excel in solving complex problems and pushing boundaries together.

If you're a recruiting agency and want to partner with us, please reach out to [email protected]. Any resume or referral submitted in the absence of a signed agreement will not be eligible for an agency fee.

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