Machine Learning Research Internship

SIG Susquehanna; Northern (KY); Hybrid; USD 55,000 - 62,000; Full time

Job summary

SIG Susquehanna offers a 10-week Machine Learning Research PhD Internship for candidates passionate about data, algorithms, and markets.

You’ll apply ML and data science to real financial problems, work with a world‑class team, and gain mentorship while bridging research and production environments.

Qualifications

• Candidate pursuing a PhD in a related field with strong ML background.
• Experience applying ML techniques in research or industry.
• Publication record in top conferences ideal.

Responsibilities

• Develop ML models to identify patterns in data and markets.
• Collaborate with ML researchers, developers, and traders.
• Design experiments and leverage GPU infrastructure for rapid iteration.
• Bridge research insights to production-ready solutions.

Skills

Research in ML

Data analysis

PyTorch

TensorFlow

Education

PhD candidate in Computer Science/ML/Statistics

Tools

PyTorch

TensorFlow

Job description

Overview

Our Machine Learning Research PhD Internship is a 10-week immersive experience designed for PhD candidates who are passionate about solving high-impact problems at the intersection of data, algorithms, and markets.

As a Machine Learning Research Intern at Susquehanna, you'll work on high-impact projects that closely reflect the challenges and workflows of our full-time research team. You'll apply your technical expertise in machine learning and data science to real-world financial problems, while developing a deep understanding of how machine learning integrates into Susquehanna's research and trading systems. You will leverage vast and diverse datasets and apply cutting-edge machine learning at scale to drive data-informed decisions in predictive modeling to strategic execution.

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. Research teams here are small and highly collaborative, ideas are debated openly, and work that proves out reaches production quickly.

What You Can Expect

• Conduct research and develop ML models to identify patterns in noisy, non-stationary data
• Work side‑by‑side with our Machine Learning team on real, impactful problems in quantitative trading and finance, bridging the gap between cutting‑edge ML research and practical implementation
• Collaborate with researchers, developers, and traders to improve existing models and explore new algorithmic approaches
• Design and run experiments using the latest ML tools and frameworks
• One‑on‑one mentorship from experienced researchers and technologists
• Participate in a comprehensive education program with deep dives into Susquehanna's ML, quant, and trading practices
• Apply rigorous scientific methods to extract signals from complex datasets and shape our understanding of market behavior
• Explore various aspects of machine learning in quantitative finance from alpha generation and signal processing to model deployment and risk‑aware decision making

What we're looking for

• Currently pursuing a PhD in Computer Science, Machine Learning, Statistics, Physics, Applied Mathematics, or a closely related field
• Proven experience applying machine learning techniques in a professional or academic setting
• Strong publication record in top‑tier conferences such as NeurIPS, ICML, or ICLR
• Hands‑on experience with machine learning frameworks, including PyTorch and TensorFlow
• Deep interest in solving complex problems and a drive to innovate in a fast‑paced, competitive environment

Why Join Us?

• Work with a world‑class team of researchers and technologists
• Access to unparalleled financial data and computing resources
• Opportunity to make a direct impact on trading performance
• Collaborative, intellectually stimulating environment with global reach

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.