At a Glance
- Tasks: Join our ML team to develop and enhance machine learning platforms for innovative trading solutions.
- Company: Dynamic finance firm with a passion for technology and collaboration.
- Benefits: Competitive salary, flexible work environment, and opportunities for professional growth.
- Other info: Exciting environment for curious minds eager to solve complex problems.
- Why this job: Make an impact in finance using cutting-edge machine learning techniques and tools.
- Qualifications: Strong mathematical background and experience with ML frameworks like PyTorch or TensorFlow.
The predicted salary is between 60000 - 80000 £ per year.
We are looking for an engineer with robust experience in machine learning and strong mathematical foundations to join our growing ML team and to help drive the direction of our ML platform. 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. We’ll rely on your in-depth knowledge of the ML ecosystem and understanding of varying approaches — whether it’s neural networks, random forests, gradient-boosted trees or sophisticated ensemble methods — to aid decision-making so we apply the right tool for the problem at hand. Your work will also focus on enhancing research workflows to tighten our feedback cycles. Successful ML engineers will be able to understand the mechanics behind various modelling techniques, while also being able to break down the mathematics behind them.
If you’ve never thought about a career in finance, you’re in good company. Many of us were in the same position before working here. While there isn’t a fixed list of qualifications we’re looking for, if you have a curious mind and a passion for solving interesting problems, we have a feeling you’ll fit right in.
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; Good candidates will be excited about things like optimisation theory, regularisation techniques, linear algebra and the like
- A passion for keeping up with the state of the art, whether that means diving into 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 wrangling an ML framework – we're fans of PyTorch, but we'd also love to learn what you know about 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 required
Machine Learning Engineer employer: Jane Street
At Jane Street, we pride ourselves on being an exceptional employer, offering a dynamic work environment where innovation thrives. Our collaborative culture fosters continuous learning and growth, allowing Machine Learning Engineers to engage in cutting-edge projects that directly impact our global trading operations. With a commitment to employee development and a passion for problem-solving, we provide the perfect platform for those looking to make meaningful contributions in the finance sector.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the ML community, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects. Whether it's a GitHub repo or a personal website, having tangible examples of your work can really set you apart from the crowd.
✨Tip Number 3
Prepare for those interviews! Brush up on your technical knowledge and be ready to discuss your thought process behind various ML techniques. Practising common interview questions can help you feel more confident when it’s your turn to shine.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our awesome team at Jane Street.
We think you need these skills to ace Machine Learning Engineer
Some tips for your application 🫡
Show Off Your Skills:Make sure to highlight your experience with machine learning and any relevant projects you've worked on. We want to see your passion for the craft, so don’t hold back on showcasing your skills!
Tailor Your Application:Take a moment to customise your application for us. Mention specific tools and techniques you’re familiar with, like PyTorch or TensorFlow, and how they relate to the role. This shows you’ve done your homework and are genuinely interested in joining our team.
Be Clear and Concise:When writing your application, keep it clear and to the point. We appreciate well-structured responses that get straight to the heart of your experience and motivations. Avoid fluff – we want to know what makes you tick!
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy – just follow the prompts and you’ll be good to go!
How to prepare for a job interview at Jane Street
✨Know Your ML Fundamentals
Brush up on your machine learning fundamentals, especially the mathematical concepts like optimisation theory and linear algebra. Be ready to discuss how these principles apply to real-world scenarios, as this will show your depth of understanding and passion for the field.
✨Showcase Your Projects
Prepare to talk about your previous projects involving ML frameworks like PyTorch or TensorFlow. Highlight specific challenges you faced, how you overcame them, and the impact your work had. This not only demonstrates your technical skills but also your problem-solving abilities.
✨Stay Current with Trends
Make sure you're up-to-date with the latest trends in machine learning. Mention any recent papers you've read or new tools you've experimented with. This shows that you have a curious mind and are genuinely interested in advancing your knowledge in the field.
✨Ask Thoughtful Questions
Prepare some insightful questions about the company's ML strategies and tools. Asking about their approach to feedback cycles or how they decide on modelling techniques can demonstrate your critical thinking and genuine interest in contributing to their team.
