Campus AI Research Engineer - Trading ML Systems

Trading Interview; New York (NY); On-site; USD 270,000 - 330,000; Full time

Job summary

Jump Trading Group is a leading research-driven trading firm applying machine learning to global financial markets. The team combines researchers, quants, and engineers to design, test, and deploy advanced ML models with a focus on performance and reliability.

The role encompasses implementing open-ended research from concept to production, improving model design, tools, and infrastructure, and collaborating across languages such as C, C++, Python, CUDA.

Qualifications

• Publication record or active contributions to AI research.
• Strong ML background with modern deep learning and language modeling.
• Strong Python and/or C++ development skills.
• Familiarity with PyTorch, JAX and/or TensorFlow.
• Intellectual curiosity, versatility and pragmatic approach.
• Ability to thrive in a team-oriented, collaborative environment.
• Ability to reason through quantitative problems and communicate with researchers.
• Reliable and predictable availability.

Responsibilities

• Apply state-of-the-art techniques to complex domains.
• Collaborate with researchers to build reusable financial ML frameworks.
• Optimize training pipelines for HPC resources.
• Integrate ML models into latency-sensitive production systems.
• Work across C/C++, Python, CUDA and other low-level GPU languages.
• Build large-scale ML systems that are observable and performant.
• Other duties as assigned or needed.

Skills

Publication record

ML background

Python/C++

ML frameworks

Curiosity

Teamwork

Quant reasoning

Reliability

Job description

Jump Trading Group is a leading research-driven trading firm applying machine learning to global financial markets. The team combines researchers, quants, and engineers to design, test, and deploy advanced ML models with a focus on performance and reliability.

The role encompasses implementing open-ended research from concept to production, improving model design, tools, and infrastructure, and collaborating across languages such as C, C++, Python, CUDA.