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.
Currently tracking 29 active AI roles, with 38 new openings in the last 4 weeks. Primary focus: Pretrain · Research.
Jane Street currently has 18 active AI-related roles in our index. The most common open titles are: Machine Learning Researcher (5), Quantitative Researcher (4), Machine Learning Engineer (3), Machine Learning Performance Engineer (3), Machine Learning Educator. Most positions are in Research and Engineering.
Jane Street's active AI hiring is concentrated in: serving infrastructure (39%), 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 (8 roles), United States (5 roles), United Kingdom (4 roles), Singapore (1 role).
Job postings at Jane Street most frequently mention: Machine Learning, Statistics, GPU Computing, Real-Time Systems, Distributed Training.
In the past 30 days, Jane Street has posted 0 new AI-related roles.
| Title | Stage | AI score |
|---|---|---|
| Machine Learning Researcher Research internship focused on applying novel ML ideas to systematic trading strategies, working with large models on nonstationary datasets in a competitive multi-agent environment. Involves end-to-end studies, new modeling paradigms, and blue-sky approaches. | Pretrain | 9 |
| Machine Learning Researcher Machine Learning Researcher to build deep learning models for trading strategies, supported by a large GPU cluster. The role involves tackling challenges like large models, nonstationary datasets, and multi-agent environments, requiring novel techniques. Researchers collaborate closely with engineers and traders, diving into market data, hyperparameter tuning, distributed training, and model behavior in production. The position requires in-depth knowledge of ML, including LLMs, image models, RL agents, recommendation systems, and classical ML, to shape the future of ML at Jane Street. Responsibilities include training next-generation models, building fundamental understanding for new markets, hiring, attending conferences, and teaching teammates. |
| Post-trainAgent |
| 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 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 |
| 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 |
| Quantitative Researcher Quantitative Researchers at Jane Street build models, strategies, and systems for pricing and trading financial instruments. The role involves working with large datasets and advanced computing infrastructure, applying various statistical and ML techniques, and collaborating closely with engineers and traders. Success requires a curious, logical, and programming-proficient individual who can adapt findings into actionable strategies. | Post-train | 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 |
| 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 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 closely with engineers and traders, working with large datasets and GPU clusters. The role is open to various statistical and machine learning techniques, emphasizing curiosity, problem-solving, and adaptability. | Data | 7 |