Campus AI Research Engineer — ML Systems & HPC

Jump Trading; Chicago (IL); On-site; USD 270,000 - 330,000; Full time

Job summary

Jump Trading Group is seeking world-class engineers to join our research, trading, and engineering teams in building state-of-the-art ML systems for quantitative finance. You will work on training pipelines on high-performance computing clusters and production-ready, low-latency inference systems.

Proficiency in Python/C++, CUDA and modern ML frameworks is highly valued, with opportunities to push AI research from concept to production in a fast-paced, collaborative environment.

Qualifications

• 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.

Responsibilities

• 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.

Skills

Python

C++

PyTorch

TensorFlow

CUDA

Job description

Jump Trading Group is seeking world-class engineers to join our research, trading, and engineering teams in building state-of-the-art ML systems for quantitative finance. You will work on training pipelines on high-performance computing clusters and production-ready, low-latency inference systems.

Proficiency in Python/C++, CUDA and modern ML frameworks is highly valued, with opportunities to push AI research from concept to production in a fast-paced, collaborative environment.