Campus AI Research Engineer: Scale ML for Global Markets

Tradermath; New York (NY); Hybrid; USD 250,000 - 300,000; Full time

Job summary

Jump Trading Group is seeking world-class engineers to collaborate with research, trading, and engineering teams to build state-of-the-art ML systems for quantitative finance in a fast-paced, collaborative environment.

You will optimize training pipelines on HPC clusters, develop low-latency inference systems, and push AI/ML capabilities from concept to production. Proficiency in Python/C++, CUDA, and related frameworks is required; international CPT/OPT eligibility is considered.

Qualifications

• 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.

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 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; reduce iteration cycle time on research.
• Other duties as assigned or needed.

Skills

Python

C++

PyTorch

JAX

TensorFlow

CUDA

GPU programming

English communication

Job description

Jump Trading Group is seeking world-class engineers to collaborate with research, trading, and engineering teams to build state-of-the-art ML systems for quantitative finance in a fast-paced, collaborative environment.

You will optimize training pipelines on HPC clusters, develop low-latency inference systems, and push AI/ML capabilities from concept to production. Proficiency in Python/C++, CUDA, and related frameworks is required; international CPT/OPT eligibility is considered.