Machine Learning Engineering Internship

Overview: Our Machine Learning Engineering Internship is a 10-week immersive experience designed for students who are passionate about building the systems at the intersection of machine learning, large-scale data, and markets. As a Machine Learning Engineering Intern, you'll work on high-impact projects that closely reflect the challenges and workflows of our full-time engineering team. You'll apply your software engineering skills to real machine learning systems while developing a deep understanding of how machine learning integrates into Susquehanna's research and trading systems. A model is useful only if it can be trained quickly, fed reliably, and run fast enough to act on - our engineers own the systems that make that true, and we scopeintern projects the same way. Susquehanna's proprietary datasets and computing infrastructure - including a rapidly growing cluster of thousands of high-end GPUs - support computationally intensive training, simulation, and rapid experimentation. Engineering teams here are small and highly collaborative, ideas are debated openly, and work that proves out reaches production quickly. What You Can Expect Build and optimize training pipelines that run across our GPU infrastructure, including distributed training for large models Work on inference and deployment — the latency, throughput, and cost of models running in production trading systems Develop the data infrastructure behind our research, moving large and noisy market datasets through ingestion, storage, and transformation Profile and benchmark machine learning workloads, and contribute to the internal libraries and open-source tools our researchers rely on every day One-on-one mentorship from experienced engineers and researchers Participate in a comprehensive education program with deep dives into Susquehanna's ML, quant, and trading practices No prior finance background required