Jane Street currently has 25 active AI-related job listings. The hiring is distributed across several stages, with serving infrastructure and data each comprising 28% of the roles, followed by pre-training at 24% and post-training at 20%. The dominant function is Research, with 18 roles, and hiring is concentrated in Hong Kong, the United States, and the United Kingdom. Frequent tech tags include model_serving, recommender_systems, and inference_infra, suggesting a focus on deploying and optimizing AI models.
Currently tracking 23 active AI roles, up 120% versus the prior 4 weeks. Primary focus: Serve · Research.
Jane Street currently has 27 active AI-related roles in our index. The most common open titles are: Machine Learning Researcher (7), Quantitative Researcher (7), Machine Learning Engineer (3), Machine Learning Performance Engineer (3), Formal Methods Engineer (2). Most positions are in Research and Engineering.
Jane Street's active AI hiring is concentrated in: serving infrastructure (26%), pre-training (26%), data (26%). 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 (9 roles), Hong Kong (9 roles), United Kingdom (8 roles), Singapore (1 role).
Job postings at Jane Street most frequently reference: model serving, agent research, fine tuning, recommender systems, frontier research.
In the past 30 days, Jane Street has posted 6 new AI-related roles.
| Title | Stage | AI score |
|---|---|---|
| Machine Learning Researcher Machine Learning Researcher at Jane Street to build deep learning models for trading strategies, supported by a large GPU cluster. The role involves training models, tuning hyperparameters, debugging distributed training, and researching novel techniques for challenges like large models, nonstationary datasets, and multi-agent environments. Researchers will shape the future of ML at Jane Street, train next-generation models, and contribute to hiring and teaching. | PretrainPost-train | 9 |
| 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 |
| Machine Learning Performance Engineer Machine Learning Performance Engineer at Jane Street, focusing on optimizing the performance of ML models for both training and inference. This role requires deep expertise in low-level systems programming, GPU optimization, and a whole-systems approach to performance, including storage and networking, within a high-frequency trading environment. | ServeData | 8 |
| Quantitative Researcher Quantitative Researcher role at Jane Street focusing on identifying market signals, analyzing data, building and testing models, and creating trading strategies. The role involves close collaboration with experienced researchers, working with large datasets and GPU clusters, and applying various statistical and ML techniques. Interns will work on projects, learn about experiment design, dataset generation, time series analysis, feature engineering, and model building for financial datasets, complemented by classes on markets and trading. | Data | 7 |
| Quantitative Researcher Quantitative Researchers at Jane Street build models, strategies, and systems for pricing and trading financial instruments. The role involves working with experienced researchers on experiment design, dataset generation, time series analysis, feature engineering, and model building for financial datasets. Researchers collaborate closely with engineers and traders, utilizing large-scale data and computing resources. The role is open to various ML techniques, from linear models to deep learning, and emphasizes curiosity, logical thinking, strong programming skills (Python), and collaboration. | Post-train | 7 |
| Quantitative Researcher Quantitative Researchers at Jane Street 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 collaborate with engineers and traders, working with large datasets and GPU clusters. The position is open to various statistical and machine learning techniques, including deep learning, and requires strong programming skills in Python and a curious, collaborative mindset. | Data | 7 |
| 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 |