Campus AI Research Engineer (Intern)
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Overview
Join Jump Trading as a Campus AI Research Engineer Intern, where you'll collaborate on cutting-edge AI/ML systems in quantitative finance. Ideal for creative thinkers eager to tackle complex challenges. Jump Trading Group is committed to world class research. We empower exceptional talents in Mathematics, Physics, and Computer Science to seek scientific boundaries, push through them, and apply cutting edge research to global financial markets. Our culture is unique. Constant innovation requires fearlessness, creativity, intellectual honesty, and a relentless competitive streak. We believe in winning together and unlocking unique individual talent by incenting collaboration and mutual respect. At Jump, research outcomes drive more than superior risk adjusted returns. We design, develop, and deploy technologies that change our world, fund start-ups across industries, and partner with leading global research organizations and universities to solve problems.
What You'll Do
- •Apply state-of-the-art techniques to complex and challenging domains.
- •Work closely with researchers and quants to build flexible and reusable frameworks for financial AI/ML.
- •Optimize training pipelines to make the best use of our HPC resources.
- •Integrate AI/ML models into production systems where latency matters.
- •Work across a mix of programming languages: C / C++ / Python / CUDA and other low-level GPU languages.
- •Build large-scale AI/ML systems that are observable, performant, and flexible.
- •Help improve productivity by reducing the iteration cycle time on research.
- •Other duties as assigned or needed.
Salary
- •The estimated base salary for this role (annualized) is $250,000 – $300,000 per year.
Skills You'll Need
- •Creative thinkers who are driven, self-motivated, and eager to solve challenging problems.
- •Proficiency in Python and/or C++.
- •Proficiency in PyTorch, JAX, TensorFlow, and/or similar frameworks.
- •Ability to thrive in a collaborative, team-oriented environment.
- •Expertise in GPU or accelerator programming (CUDA, Triton, SYCL, ROCm, or equivalent).
- •Experience building AI/ML systems at scale (hundreds of TBs of training data, low-latency or high-throughput inference requirements).
- •Excellent written and verbal communication skills in English.
- •Reliable and predictable availability.
- •INTERNATIONAL STUDENTS are encouraged to apply. We accept students eligible for CPT/OPT and we sponsor work visas for full-time positions.