Machine Learning Systems Engineer: Data

Susquehanna International; Bala Cynwyd (PA); On-site; USD 140,000 - 190,000; Full time

Job summary

Susquehanna International is seeking a Machine Learning Systems Engineer to help build the data infrastructure powering AI research. You will develop reliable, high‑performance systems for handling large and complex datasets, emphasizing scalability and reproducibility.

You’ll partner with researchers to support experimental workflows and translate evolving needs into production‑ready solutions. The role focuses on optimizing compute performance across distributed systems and building

Qualifications

• 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 software engineering in Python.
• Understanding of AI/ML workloads, including data preprocessing, feature engineering, and model evaluation.

Responsibilities

• 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 AI experimentation.
• Optimize resource utilization across distributed computing infrastructure through profiling, benchmarking, and systems‑level improvements.
• Implement low‑latency high‑throughput sampling for models.

Skills

Data pipelines

ETL at scale

ML infrastructure

Performance optimization

Systems programming

Python software engineering

AI/ML workflows

Job description

Overview

We’re looking for a Machine Learning Systems Engineer to help build the data infrastructure that powers our AI 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.

Overview

We’re looking for a Machine Learning Systems Engineer to help build the data infrastructure that powers our AI 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 shaping the future of AI at Susquehanna — 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 AI 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 software engineering in python
• Understanding of AI/ML 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.