Machine Learning Systems Engineer

Overview

We’re looking for a versatile Machine Learning Systems Engineer to help build and optimize the core infrastructure that supports our AI research. This role involves working across the stack—from data processing and training efficiency to low-level GPU programming and performance tooling. You'll contribute to systems that are reliable, scalable, and tuned for high performance, while enabling researchers to better understand and improve their models. Ideal candidates are comfortable navigating complex systems, enjoy working across domains, and bring a strong engineering mindset paired with an interest in supporting innovative machine learning efforts.

What You Could Work On:

• Design and implement high-performance, reliable, and reproducible data pipelines for large-scale ML workloads
• Collaborate with researchers to develop systems-efficient models and architectures
• Optimize training efficiency using cutting-edge techniques and custom GPU kernels
• Build observability and benchmarking tools to analyse and improve model and system performance
• Create secure, sandboxed execution environments
• Develop tools to streamline distributed training and improve resource utilization across our compute infrastructure
• Implement low-latency, high-throughput sampling systems for model inference

What we’re looking for

• Experience building or maintaining data pipelines and ETL processes
• Familiarity with systems-level programming and performance optimization
• Proficiency in Python and comfort working with large codebases
• Exposure to GPU programming or custom kernel development is a plus
• Interest in observability, benchmarking, or performance tooling at scale
• Understanding of ML workflows, including training and inference
• Experience working with distributed systems or compute infrastructure
• Comfortable working in fast-evolving, cross-disciplinary environments
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  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.