Back to search
EngineeringNot provided by source

Campus AI Research Engineer - Deep Learning (Intern)

Jump Trading · Not provided by source

Apply
Last seen by MeritLog September 10, 2026Source: GreenhouseSource version: greenhouse-job-board-v1

MeritLog read this listing from Jump Trading's Greenhouse job board and last checked it on September 10, 2026.

Source: the employer's Greenhouse job board. Open the original listing for current details.

Job details

Work model
Not provided by source
Salary
From $300,000 per year
Location
Chicago; New York

Hiring context

How this role compares at Jump Trading

Jump Trading has 106 live roles in MeritLog’s catalog across 5 job families, and 48 of them are in engineering. 36 of those listings publish a pay range, a disclosure rate of 34%.

This role's posted range of From $300,000 per year sits above 77% of the 35 other Jump Trading roles quoted over the same currency and period.

Jump Trading concentrates this hiring in:

Counted across the job boards MeritLog tracks, at the time this page was served. Pay comparisons use only listings that publish a complete range in the same currency and period.

What the role asks for

What you'd 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.

What they're asking for

  • Strong publication record at ICML, ICLR, AAAI, NeurIPS, UAI, KDD, or equivalent and/or contributions to open-source AI researchSkill
  • Strong general ML background with exposure to modern deep learning techniques and/or language modeling architectures (e.g. transformers, SSMs)Skill
  • Solid development skills in Python and/or C++Skill
  • Familiarity with ML libraries/frameworks such as PyTorch, JAX, and/or TensorFlowSkill
  • Intellectual curiosity, versatility, and originality combined with a pragmatic outlookSkill
  • Ability to thrive in a collaborative, team-oriented environmentSkill
  • Ability to reason through quantitative problems and communicate effectively with trading researchersSkill
  • Reliable and predictable availabilitySkill
  • Experience with HPC and distributed large model trainingSkillPreferred
  • Experience with GPU performance optimization (CUDA or ROCm)SkillPreferred
  • Experience with end-to-end model developmentSkillPreferred
  • Strong opinions on best practices in ML research, tooling, and/or infrastructureSkillPreferred

Parsed by MeritLog from the employer’s own posting. The full description follows below.

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. We are seeking research scientists with a demonstrated ability to apply machine learning to achieve state-of-the-art capabilities in complex and challenging domains. The ideal person for this role will be capable of implementing an open-ended research project from concept to production and continuously improving model design, tools, and infrastructure. Potential projects may target any area of the quantitative research and monetization process. We believe that successful research efforts require a fluid mix of skills including AI/ML expertise, engineering pragmatism, statistics, and market intuition. 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.

Privacy choices

Analytics and advertising stay off unless you allow them. Private data stays out.

Read the privacy notice