Role at a glance
- Job function
-
Education & Training Curriculum Development & Instructional Design Technical & Vocational Training
- Salary
- Not Disclosed
- Location
- New York, New York, United States
- Work arrangement
- On-site
- Employment
- Full-time
- Experience
- We’re excited to talk to people who have experience teaching ML topics in a university or an industry setting.
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Role Summary
The Machine Learning Educator helps teach machine learning at Jane Street and maintain and grow its ML educational programs and classes. The role combines teaching and curriculum development with coding as part of machine learning research.
What You'll Do
- Teach machine learning topics, including introductory ML, efficient use of AI assistants, the internal stack for training models, and...
- Maintain and grow machine learning educational programs and classes.
- Develop curricula.
- Mentor and help develop the teaching skills of other people involved in teaching.
- Write code as part of machine learning research and build an understanding of the technology stack through hands-on work.
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
Skilled and effective teacher; effective writer and presenter; able to write code and willing to spend a significant fraction of time doing so as part of machine learning research; interested in mentoring other teachers and developing curricula.
Preferred
- Experience teaching ML topics in a university or an industry setting.
Original job description
Content provided by the employer
Original job description
Content provided by the employer
About the Position
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. Our ML team is full of people with a shared love for the craft of software engineering, and for designing APIs and systems that are delightful to use.
Education is also a big focus for us. We believe that continued learning and exploration will play an essential role in supporting our growth. As Machine learning permeates through every part of our stack, we want to invest more.
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 [email protected].
About the company
Jane Street
Large Enterprise
Jane Street is a global trading firm that specializes in quantitative and algorithmic trading across various asset classes, including equities, options, and fixed income. Founded in 2000, the company leverages advanced technology and data analytics to drive its trading strategies while maintaining a strong commitment to risk management and collaboration. Known for its dynamic and intellectually stimulating work environment, Jane Street also places a high value on continuous learning and professional development, making it an attractive workplace for individuals interested in finance, mathematics, and computer science.