At a Glance
- Tasks: Build cutting-edge ML systems and collaborate with top researchers in finance.
- Company: Jump Trading Group, a leader in innovative financial research.
- Benefits: Competitive pay, work visa sponsorship, and a dynamic team environment.
- Other info: International students welcome; excellent growth opportunities in a fast-paced setting.
- Why this job: Tackle complex problems and make a real impact in quantitative finance.
- Qualifications: Proficiency in Python/C++, experience with ML frameworks, and a collaborative spirit.
The predicted salary is between 22500 - 27500 £ per year.
Jump Trading Group is committed to world class research.
We empower exceptional talents in Mathematics, Physics, and Computer Science to seek scientific boundaries, push through them, and apply cutting edge research to global financial markets.
Our culture is unique.
Constant innovation requires fearlessness, creativity, intellectual honesty, and a relentless competitive streak.
We believe in winning together and unlocking unique individual talent by incenting collaboration and mutual respect.
At Jump, research outcomes drive more than superior risk adjusted returns.
We design, develop, and deploy technologies that change our world, fund start-ups across industries, and partner with leading global research organizations and universities to solve problems.
Our trading teams are each comprised of a dynamic group of traders, quantitative researchers, and engineers who work together to examine the global markets, seeking to understand the complexities of various traded products and exchanges.
They leverage their impeccable statistical analysis and data mining skills, using the results of their research to make forecasts and develop profitable predictive trading models.
We are seeking world-class engineers to collaborate with our research, trading, engineering teams to build state-of-the-art ML systems that solve some of the most complex problems in quantitative finance.
Whether optimizing training pipelines on high-performance computing clusters, developing low-latency inference systems, or pushing the boundaries of AI research from concept to production, you'll have the opportunity to work on impactful projects in a fast-paced, collaborative environment.
If you are driven by technical challenges, eager to work with large-scale systems, and passionate about advancing ML capabilities, we want to meet you.
What you'll do
- Apply state-of-the-art techniques to complex and challenging domains.
- Work closely with researchers and quants to build flexible and reusable frameworks for financial ML.
- Optimize training pipelines to make the best use of our HPC resources.
- Integrate ML models into production systems where latency matters.
- Work across a mix of programming languages: C / C++ / Python / CUDA and other low-level GPU languages.
- Build large scale ML systems that are observable, performant, and flexible. Help improve productivity by reducing the iteration cycle time on research.
- Other duties as assigned or needed.
This role covers a wide gamut of potential projects and skills.
We don't expect everyone to have all of these, but for the applicable areas we are looking for deep technical expertise.
Skills you'll need
- Creative thinkers who are driven, self-motivated, and eager to solve challenging problems
- Proficiency in Python and/or C++
- Proficiency in Pytorch, JAX, Tensorflow or other DL library.
- Ability to thrive in a collaborative, team-oriented environment
- Expertise in GPU or Accelerator programming (CUDA, Triton, SYCL, ROCm or equivalent)
- Experience building ML systems at large scale (hundreds of TBs of training data, low latency or high throughput inference requirements)
- Excellent written and verbal communication skills in English
- Reliable and predictable availability required
INTERNATIONAL STUDENTS are encouraged to apply. We sponsor work visas for full-time positions.
Jump Trading Group is committed to world class research.
We empower exceptional talents in Mathematics, Physics, and Computer Science to seek scientific boundaries, push through them, and apply cutting edge…
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Campus ML Research Engineer (Intern) employer: Trading Interview
Tower Research Capital is an exceptional employer that fosters a dynamic and collaborative work culture, where innovation and rigorous experimentation are at the forefront. Located in a vibrant financial hub, employees benefit from cutting-edge technology and resources, alongside ample opportunities for professional growth and development within the fast-paced world of quantitative trading. Join us to be part of a team that values your contributions and rewards your success in a meaningful way.
StudySmarter Expert Advice🤫
We think this is how you could land Campus ML Research Engineer (Intern)
✨Join Data-Science Meetups
Get yourself along to local data-science meetups or workshops. They're goldmines for networking, and you'll learn from industry pros who might just point you in the direction of internships. Plus, discussing the latest trends with like-minded individuals can really amp up your game.
✨Utilise University Career Services
Check in with your uni's career services since they often have connections with companies looking for interns. They might even organise information sessions with firms, which can be a great chance for you to learn more about potential internships and make some key contacts.
✨Show Off Your Stuff on GitHub
If you're into data science, having a GitHub profile with your projects is essential. Make sure your portfolio is public and showcases your best work! Recruiters love to see your coding skills and problem-solving approach, and it’s a brilliant way to stand out.
✨Apply Directly on Our Website
Don’t forget to check out the internships listed on our site! It's always a good idea to apply directly through our website because it makes your application easier for our team to find, and you might just catch the hiring manager’s eye by showcasing exactly what you're passionate about in data science.
We think you need these skills to ace Campus ML Research Engineer (Intern)
Some tips for your application 🫡
Show Off Your Technical Skills:For a data science internship, we want to see those analytical skills shine! List your programming languages, like Python or R, and make sure to highlight any relevant projects or courses you've completed. If you've dabbled with tools like Pandas, NumPy, or machine learning algorithms, don’t hold back – include those in your CV!
Share Your Curiosity in Your Cover Letter:As an intern, your motivation and eagerness to learn are key! In your cover letter, talk about specific data science concepts that excite you and how this internship at Trading Interview will help you grow. Share what you hope to achieve and how you plan to tackle real-world data problems - we love enthusiasm!
Include Any Relevant Certifications:If you've earned any certifications, such as from Coursera or DataCamp, make sure to include these in your application. They show us that you're proactive and committed to expanding your data science skillset. This could make a real difference in how we assess your application!
Keep It Relevant and Concise:Remember, as an intern, you don’t need to have decades of experience. Focus on showcasing relevant coursework, personal projects, or even related volunteer work in data science. Keep your CV and cover letter concise but impactful – we appreciate clear and straightforward communication!
How to prepare for a job interview at Trading Interview
✨Brush Up on Your Coding Skills
As a data science intern, you might get grilled on your programming skills. Expect to tackle some coding challenges using languages like Python or R. We recommend practising basic algorithms or data manipulation tasks so you can show off your tech skills with confidence.
✨Show Off Your Projects
Prepare to discuss any projects you’ve done, whether in your studies or on your own time. Having a strong portfolio of data analyses or machine learning models will really set you apart. We can use platforms like GitHub to showcase your work to impress Trading Interview.
✨Know Your Stats and ML Basics
Brush up on your statistics and machine learning concepts because interviewers love to dig into this! Be ready to explain your understanding of algorithms or how you would approach a given data problem. This will highlight your theoretical background alongside your practical skills.
✨Be Eager to Learn and Adapt
Internships are all about potential and growth. Make sure you convey your eagerness to learn and adapt to new tools or methodologies. Show Trading Interview that you’re not just looking for experience, but that you're keen to contribute and grow within the team.
