Machine Learning Systems Engineer: Data
About The Position
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.
Requirements
- 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 our distributed computing infrastructure through profiling, benchmarking, and systems-level improvements
- Implement low-latency high-throughput sampling for models
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Education Level
No Education Listed
Number of Employees
1,001-5,000 employees
