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.
Currently tracking 29 active AI roles, with 38 new openings in the last 4 weeks. Primary focus: Pretrain · Research.
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 Machine Learning Researcher to build deep learning models for trading strategies, leveraging large-scale GPU clusters and novel techniques to address challenges in nonstationary datasets and multi-agent environments. The role involves training next-generation models, understanding new markets, and contributing to hiring and knowledge sharing. | PretrainAgent | 9 |
| Machine Learning Performance Engineer Machine Learning Performance Engineer role focused on optimizing the performance of ML models for both training and inference. Requires deep low-level systems programming and GPU knowledge, debugging skills, and experience with ML libraries and distributed training. | Serve |
| 9 |
| Machine Learning Researcher Machine Learning Researcher to build deep learning models for trading strategies, leveraging a large GPU cluster and tackling challenges like large models, nonstationary datasets, and multi-agent environments. The role involves training models, architecting systems, and researching novel techniques across various ML domains (LLMs, image models, RL agents, recommendation systems, classical ML). Responsibilities include training next-gen models, building fundamental understanding, hiring, attending conferences, and teaching teammates. | PretrainPost-train | 9 |
| Senior Weather Analyst/ML Researcher Research role focused on applied research in weather prediction, embedded within a commodities trading desk. Requires strong programming skills (Python), expertise in atmospheric science topics, and experience with AI models. The role involves challenging the limits of atmospheric predictability and exploring new research directions. | Pretrain | 7 |
| Quantitative Researcher Jane Street is seeking Quantitative Researchers to build models and systems for pricing and trading financial instruments. The role involves working with large datasets and advanced computing infrastructure, applying various statistical and ML techniques, and collaborating closely with engineers and traders. The focus is on developing actionable strategies based on data analysis and model building. | Post-train | 7 |
| Machine Learning Engineer Machine Learning Engineer at Jane Street to drive the direction of their ML platform, focusing on building and maintaining training and inference infrastructure, enhancing research workflows, and applying ML to financial trading. Requires strong mathematical foundations and experience with ML frameworks. | ServeData | 7 |
| Quantitative Researcher Jane Street is seeking Quantitative Researchers to build models, strategies, and systems for pricing and trading financial instruments. The role involves applying expertise in experiment design, dataset generation, time series analysis, feature engineering, and model building to financial datasets. Researchers will collaborate with engineers and traders, working with large datasets and a significant GPU cluster. The position is open to various statistical and machine learning techniques, emphasizing curiosity and the ability to integrate findings into actionable trading strategies. | Serve | 7 |