About this role
Job title: AI Research Scientist | Research & Development
About the Role Jump Trading Group is investing in world-class AI research to generate signals from unstructured data and apply frontier AI to global financial markets. Our AI team comprises quantitative researchers, engineers, and ML experts leading LLM research and applications, collaborating with trading teams and global research partners. This role focuses on applying machine learning to advance state-of-the-art capabilities in complex domains and bringing research outcomes into production.
What You'll Do
- Lead open-ended ML research projects from concept to production, identifying compelling problems aligned with current and projected LLM capabilities, and collaborating with trading teams to understand requirements and constraints.
- Continuously improve model design, tools, and infrastructure; explore areas across the quantitative research process with potential firmwide application.
- Balance ML expertise, engineering pragmatism, and market intuition; excel in at least one area while being competent in a second and enthusiastic about the third.
- Perform other duties as assigned or needed.
What We're Looking For
- 5+ year track record of creating ML systems with real metrics & impact in industry and/or academia
- Strong general ML background with exposure to language modeling architectures (e.g. transformers, SSMs)
- Solid development skills in Python and/or C++
- Familiarity with ML libraries/frameworks such as PyTorch (preferred), TensorFlow, and/or JAX
- Intellectual curiosity, versatility, and originality combined with a pragmatic outlook
- Ability to reason through quantitative problems and communicate effectively with trading researchers
- PhD, or Master's degree in Computer Science, Mathematics, (or related subject)
- Strong publications record at ICML, ICLR, AAAI, NeurIPS, UAI, KDD, or equivalent
- Reliable and predictable availability
Nice to Have
- Experience with HPC and distributed large model training
- Experience with GPU performance optimization (CUDA or ROCm)
- Experience with end-to-end model development, especially in LLMs
- Prior academic publications and/or contributions to open-source AI research
- Strong opinions on best practices in ML research, tooling, and/or infrastructure
Compensation & Benefits
- Annual Base Salary Range: $200,000—$300,000 USD
- Discretionary bonus eligibility
- Medical, dental, and vision insurance
- HSA, FSA, and Dependent Care options
- Employer Paid Group Term Life and AD&D Insurance
- Voluntary Life & AD&D insurance
- Paid vacation plus paid holidays
- Retirement plan with employer match
- Paid parental leave
- Wellness Programs