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, 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 Machine Learning Researcher to build deep learning models for trading strategies, leveraging a large GPU cluster. The role involves training models, architecting systems, and tackling challenges like large models, nonstationary datasets, and multi-agent environments. Researchers will shape the future of ML at Jane Street, train next-gen models, and contribute to hiring and teaching. |
| PretrainAgent |
| 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, leveraging large-scale GPU clusters and novel techniques to address challenges in nonstationary datasets and multi-agent environments. The role involves training next-generation models, understanding new markets, and contributing to hiring and knowledge sharing. | PretrainAgent | 9 |
| Machine Learning Researcher Machine Learning Researcher at Jane Street to build deep learning models for trading strategies, leveraging large-scale GPU clusters and tackling challenges like large models, nonstationary datasets, and multi-agent environments. The role involves training next-generation models, developing fundamental understanding for new markets, and contributing to hiring and knowledge sharing. | Post-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 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 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 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 |
| 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 Researcher Jane Street is seeking Machine Learning Researchers to build deep learning models for trading strategies, leveraging a large GPU cluster. The role involves training models, architecting systems, and running trading strategies in a competitive multi-agent environment with nonstationary datasets, requiring novel techniques. Researchers will shape the future of ML at Jane Street by training next-generation models and tackling new markets. | Post-trainAgent | 8 |
| 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 |
| 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 |
| 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 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 Jane Street is seeking Quantitative Researchers to build models 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. The focus is on developing actionable strategies based on data analysis and model building. | Post-train | 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 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 |
| 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 |
| 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 |
| 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 |