Campus AI Research Engineer Deep Learning Intern

Jump Trading; New York (NY); On-site; USD 260,000 - 360,000; Full time

Job summary

Jump Trading Group is seeking exceptional ML researchers and engineers to apply state-of-the-art techniques to complex financial domains. You will collaborate with researchers and quants to build flexible ML frameworks and optimize training pipelines to leverage HPC resources.

You will work across Python, C++, CUDA and related ML libraries, building large-scale, observable systems and integrating models into latency-sensitive production environments.

Qualifications

• Strong ML background with deep learning or language modeling experience.
• Solid development skills in Python and C++.
• Experience with HPC and distributed large model training.
• Strong publication record at major ML conferences or contributions to open-source AI research.

Responsibilities

• Apply state-of-the-art ML techniques to complex and challenging domains.
• Work closely with researchers and quants to build flexible and reusable ML frameworks for financial ML.
• Optimize training pipelines to make the best use of HPC resources.
• Integrate ML models into production systems where latency matters.
• Work across Python, C++, CUDA and other low-level GPU languages.
• Build large-scale ML systems that are observable, performant, and flexible.

Skills

Python

C++

CUDA

ML frameworks

Collaboration

Research communication

Tools

PyTorch

JAX

TensorFlow

Job description

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.

Our trading teams are each comprised of a dynamic group of traders, quantitative researchers, and engineers who work together to examine the global markets, seeking to understand the complexities of various traded products and exchanges. They leverage their impeccable statistical analysis and data mining skills, using the results of their research to make forecasts and develop profitable predictive trading models.

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 ML.
• Optimize training pipelines to make the best use of our HPC resources.
• Integrate 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 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 You'll Need:

• Strong publication record at ICML, ICLR, AAAI, NeurIPS, UAI, KDD, or equivalent and/or contributions to open-source AI research
• Strong general ML background with exposure to modern deep learning techniques and/or language modeling architectures (e.g. transformers, SSMs)
• Solid development skills in Python and/or C++
• Familiarity with ML libraries/frameworks such as PyTorch, JAX, and/or TensorFlow
• Intellectual curiosity, versatility, and originality combined with a pragmatic outlook
• Ability to thrive in a collaborative, team-oriented environment
• Ability to reason through quantitative problems and communicate effectively with trading researchers
• Reliable and predictable availability

Bonus Points:

• Experience with HPC and distributed large model training
• Experience with GPU performance optimization (CUDA or ROCm)
• Experience with end-to-end model development
• Strong opinions on best practices in ML research, tooling, and/or infrastructure

INTERNATIONAL STUDENTS are encouraged to apply. We accept students eligible for CPT/OPT and we sponsor work visas for full-time positions.

The estimated base salary for this role (annualized) is $300,000 per year.