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
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.
Currently tracking 23 active AI roles, up 120% versus the prior 4 weeks. Primary focus: Serve · Research.
| Title | Stage | AI score |
|---|---|---|
| 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 |