Jane Street
Quant · Quantitative trading firm
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.
Quant · Quantitative trading firm
Currently tracking 29 active AI roles, with 38 new openings in the last 4 weeks. Primary focus: Pretrain · Research.
Jane Street currently has 7 active AI-related roles in our index. The most common open titles are: Machine Learning Researcher (3), Machine Learning Engineer (2), Quantitative Researcher, Software Engineer. Most positions are in Research and Engineering.
Jane Street's active AI hiring is concentrated in: serving infrastructure (43%), pre-training (43%), data (14%). 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: United States (2 roles), United Kingdom (2 roles), Hong Kong (2 roles), Singapore (1 role).
Job postings at Jane Street most frequently mention: Machine Learning, scikit-learn, TensorFlow, Python, PyTorch.
| Title | Stage | AI score |
|---|---|---|
| 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 |
| 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 |
| Machine Learning Researcher Research role focused on building deep learning models for trading strategies, leveraging a large GPU cluster. The role involves training models, architecting systems, and understanding market data in a competitive multi-agent environment, pushing for novel techniques across various ML domains like LLMs, image models, RL agents, and recommendation systems. | PretrainAgent | 9 |
| Machine Learning Engineer Jane Street is seeking a Machine Learning Engineer to join their ML team and drive the direction of their ML platform. The role involves building and maintaining training and inference infrastructure, enhancing research workflows, and applying ML to financial trading. Requires a strong mathematical background and expertise in ML frameworks. | ServeData | 7 |
| Machine Learning Engineer Jane Street is seeking a Machine Learning Engineer with a strong mathematical background to join their ML team and drive the direction of their ML platform. The role involves applying various ML techniques to aid decision-making in their trading environment, enhancing research workflows, and building/maintaining training and inference infrastructure to move concepts to production. | Serve | 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 |