Job Description
35 days ago
We are looking for an experienced engineer with a strong background in machine learning and mathematical foundations to enhance our ML platform at Jane Street.
Our trading environment is a dynamic, rapid-feedback platform for ML experimentation, allowing us to incorporate new ideas efficiently. The ML team is comprised of software engineers who share a passion for designing user-friendly APIs and systems.
As a key member of the team, you will rely on your knowledge of the ML ecosystem and understanding of various approaches to aid decision-making and apply the right tool for the problem at hand. Your work will also focus on optimizing research workflows to tighten our feedback cycles. Successful engineers will be able to understand the mechanics behind various modelling techniques and break down the mathematics behind them.
We're looking for someone with:
• Experience building and maintaining training and inference infrastructure, with an understanding of what it takes to move from concept to production
• A strong mathematical background, with expertise in optimisation theory, regularisation techniques, linear algebra, and similar
• A passion for staying up-to-date with the state of the art, whether that means reading academic papers, experimenting with the latest hardware, or reading the source of a new machine learning package
• A proven ability to create and maintain an organised research codebase that produces robust, reproducible results while maintaining ease of use
• Expertise in wrangling an ML framework, such as PyTorch, Jax, TensorFlow, or others
• An inventive approach and the willingness to ask hard questions about whether we're taking the right approaches and using the right tools
• Fluency in English
Our trading environment is a dynamic, rapid-feedback platform for ML experimentation, allowing us to incorporate new ideas efficiently. The ML team is comprised of software engineers who share a passion for designing user-friendly APIs and systems.
As a key member of the team, you will rely on your knowledge of the ML ecosystem and understanding of various approaches to aid decision-making and apply the right tool for the problem at hand. Your work will also focus on optimizing research workflows to tighten our feedback cycles. Successful engineers will be able to understand the mechanics behind various modelling techniques and break down the mathematics behind them.
We're looking for someone with:
• Experience building and maintaining training and inference infrastructure, with an understanding of what it takes to move from concept to production
• A strong mathematical background, with expertise in optimisation theory, regularisation techniques, linear algebra, and similar
• A passion for staying up-to-date with the state of the art, whether that means reading academic papers, experimenting with the latest hardware, or reading the source of a new machine learning package
• A proven ability to create and maintain an organised research codebase that produces robust, reproducible results while maintaining ease of use
• Expertise in wrangling an ML framework, such as PyTorch, Jax, TensorFlow, or others
• An inventive approach and the willingness to ask hard questions about whether we're taking the right approaches and using the right tools
• Fluency in English
More jobs from Jane Street
Software Engineer
Central and Western, Hong Kong
7 days ago
Full Time
Onsite
Technology, Information and Media
Cybersecurity Detection and Response Analyst
Jane Street
Cybersecurity
Central and Western, Hong Kong
7 days ago
Full Time
Onsite
Technology, Information and Media
Artificial Intelligence Specialist
Jane Street
Data Science
Central and Western, Hong Kong
7 days ago
Full Time
Onsite
Technology, Information and Media
Financial Reporting Accountant
Jane Street
Cybersecurity
Central and Western, Hong Kong
7 days ago
Full Time
Onsite
Technology, Information and Media
Cybersecurity Detection and Response Analyst
Jane Street
Cybersecurity
Central and Western, Hong Kong
7 days ago
Full Time
Onsite
Technology, Information and Media
More jobs like this
🎉 Got an interview?