Jane Street
Quant · Quantitative trading firm
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.
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 |
|---|---|---|
| Senior Weather Analyst/ML Researcher Applied research role on a weather team, embedded within a commodities trading desk, focusing on atmospheric predictability challenges. Requires strong Python programming and expertise in atmospheric science topics, with AI model experience preferred. | Data | 7 |
| Machine Learning Educator Jane Street is seeking an experienced Machine Learning Educator to develop and maintain their ML educational programs. This role involves teaching general ML, AI assistants, internal training stacks, and performance reasoning. The educator will also write code for ML research, mentor other teachers, and develop curricula. Experience teaching ML in a university or industry setting is required. | Data | 7 |
| Quantitative Researcher |
| Data |
| 7 |