Currently tracking 29 active AI roles, with 38 new openings in the last 4 weeks. Primary focus: Pretrain · Research.
Jane Street has 31 active AI-related job listings. The majority of these roles are focused on data (29%) and pre-training (26%), with a significant number also in serving infrastructure (23%). Research roles represent the largest functional area, with hiring concentrated in Hong Kong and the United States. Frequent tech tags include fine-tuning, model serving, and pretraining.
Jane Street currently has 18 active AI-related roles in our index. The most common open titles are: Machine Learning Researcher (5), Quantitative Researcher (4), Machine Learning Engineer (3), Machine Learning Performance Engineer (3), Machine Learning Educator. Most positions are in Research and Engineering.
Jane Street's active AI hiring is concentrated in: serving infrastructure (39%), pre-training (28%), data (28%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Jane Street is hiring AI talent in: Hong Kong (8 roles), United States (5 roles), United Kingdom (4 roles), Singapore (1 role).
Job postings at Jane Street most frequently mention: Machine Learning, Statistics, GPU Computing, Real-Time Systems, Distributed Training.
In the past 30 days, Jane Street has posted 0 new AI-related roles.
| Title | Stage | AI score |
|---|---|---|
| Machine Learning Researcher Jane Street is seeking a Machine Learning Researcher to work on projects combining novel ML ideas with systematic trading strategies. The role involves end-to-end studies, exploring new modeling paradigms, and applying state-of-the-art techniques to challenging problems in finance, utilizing large-scale data and computing resources. The position is for a PhD student or postdoc with empirical ML research experience, strong logical and mathematical thinking, and Python implementation skills. | PretrainPost-train | 9 |
| Machine Learning Researcher Machine Learning Researcher to build deep learning models for trading strategies, supported by a large GPU cluster. The role involves training models, architecting systems, and studying model behavior in production, with a focus on novel techniques for challenges like large models, nonstationary datasets, and multi-agent environments. Responsibilities include hiring, attending conferences, and teaching. |
| PretrainPost-train |
| 9 |