Jane Street is hiring a Machine Learning Educator in Machine Learning — New York, New York, United States. The overview below is synthesized from the employer posting on janestreet.com: factual requirements and scope are preserved, but prose is rewritten with editorial context. Verify details and apply via the employer link.
About the Position
Company context from the listing:
We’re looking for an experienced and skilled educator to help us teach people at Jane Street about machine learning.
Machine learning is a critical pillar of Jane Street's global business. Our ever-evolving trading environment serves as a unique, rapid-feedback platform for ML experimentation, allowing us to incorporate new ideas with relatively little friction.
Education is also a big focus for us. We believe that continued learning and exploration will play an essential role in supporting our growth.
The ML Educator will be instrumental in maintaining and growing our ML educational programs and classes, spanning topics such as an introduction to general ML, efficient use of AI assistants, our internal stack for training models, and how to reason about performance. We’re looking for someone who:
- Is a skilled, effective, and experienced teacher. Part of that means being an effective writer and presenter.
- Is good at writing code, and is excited to spend a significant fraction of their time doing so as part of our machine learning research. The job requires developing an understanding of our technology stack, and the best way to build that understanding is by doing.
- Is a great mentor to other budding teachers. Part of the job is going to be teaching and developing curricula. But an equally important part is going to be helping other people involved in teaching to grow their skills.
We’re excited to talk to people who have experience teaching ML topics in a university or an industry setting.
If you're a recruiting agency and want to partner with us, please reach out to agency-partnerships@janestreet.com.
Build a standout application
For the Machine Learning Educator at Jane Street, reviewers look for concise evidence over buzzwords. Mirror the language of the posting sparingly, quantify support or delivery outcomes, and show how you handled ambiguity, time-zone collaboration and user empathy. Keep your resume to impact, keep your cover note to one page, and link to artifacts — tickets resolved, docs shipped, dashboards owned — that prove you can operate in a fast-moving Web3 team. Prepare to discuss a time you turned a confusing user report into a clear fix and how you measure quality in support and operations.
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