Jane Street
Quant · Quantitative trading firm
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.
Quant · Quantitative trading firm
Currently tracking 23 active AI roles, with 16 new openings in the last 4 weeks. Primary focus: Serve · Research.
Jane Street currently has 25 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), Senior Weather Analyst/ML Researcher (2). Most positions are in Research and Engineering.
Jane Street's active AI hiring is concentrated in: serving infrastructure (28%), 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 (9 roles), United States (8 roles), United Kingdom (7 roles), Singapore (1 role).
Job postings at Jane Street most frequently reference: model serving, fine tuning, recommender systems, frontier research, pretraining.
In the past 30 days, Jane Street has posted 4 new AI-related roles.
| Title | Stage | AI score |
|---|---|---|
| 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. | ServeData | 9 |
| Machine Learning Performance Engineer Seeking an engineer with low-level systems programming and optimization experience to join the ML team, focusing on optimizing the performance of ML models for both training and inference in a real-time trading environment. This role requires a deep understanding of GPU architecture, networking, and distributed systems to ensure efficient large-scale training and low-latency, high-throughput inference. | ServeData |
| 8 |
| 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 |
| 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 |
| 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 |