At a Glance
- Tasks: Collaborate on real-world ML projects with mentorship from experienced professionals.
- Company: Jane Street, a leader in finance and machine learning innovation.
- Benefits: Gain hands-on experience, access to cutting-edge technology, and mentorship.
- Other info: Dynamic environment with opportunities for growth and learning.
- Why this job: Dive into the exciting world of finance and machine learning while making a real impact.
- Qualifications: Undergraduate or postgraduate student with ML experience and strong programming skills.
The predicted salary is between 100 - 100 £ per hour.
About the Position
Our goals are to give you a real sense of what it's like to work at Jane Street as a Machine Learning Engineer while also providing a truly unparalleled educational experience.
You'll be paired with full-time employees who act as mentors, collaborating with you on real-world ML projects we actually need done.
Many classes and activities are shared with our Software Engineering interns, while others focus specifically on machine learning applications and techniques.
Machine learning is a critical pillar of Jane Street's global business.
Our ever-changing trading environment serves as a unique, rapid-feedback platform for ML experimentation, allowing us to incorporate new ideas with relatively little friction.
If you’d like to learn more, you can have a look at our Machine Learning page.
During the programme, you'll work on projects mentored closely by the full-time employees who designed them.
Some projects consider big-picture questions that we're still trying to figure out, while others involve building something new.
You will get access to our growing GPU cluster containing thousands of H100/H200/B200s and gain an understanding of the differences between textbook machine learning and its application to noisy financial data.
The interview process follows the same structure as our Software Engineering Intern interviews, with one key addition: after your initial technical coding interview over Zoom, you'll have an on-site interview with 2-4 technical rounds, including one dedicated to assessing ML engineering skills.
Learn more about Jane Street's internship programme here.
About You
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.
If you have a curious mind, a collaborative spirit, and a passion for solving interesting problems, we have a feeling you'll fit right in.
We're more interested in how you think and learn than what you currently know.
You should be: An undergraduate, postgraduate or Ph D student with practical experience training an ML model, working on an ML library, or optimising an ML workflow A top-notch programmer with a love for technology Intellectually curious, collaborative, and eager to learn Humble and unafraid to ask questions and admit mistakes Fluent in English
Machine Learning Engineer in London employer: Jane Street
At Jane Street, we pride ourselves on being an exceptional employer, fostering a vibrant work culture that prioritises collaboration and employee engagement. Our London office offers a dynamic environment where the Events Management Specialist will play a crucial role in enhancing team connections through thoughtfully curated events, while benefiting from ample opportunities for professional growth and development. With a strong emphasis on support and innovation, we ensure our employees feel valued and excited to contribute to our collective success.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer in London
✨Get Involved in Data Science Meetups
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✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Machine Learning Engineer at Jane Street.
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We think you need these skills to ace Machine Learning Engineer in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Jane Street, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Jane Street. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Jane Street
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Jane Street!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
