At a Glance
- Tasks: Tackle complex machine learning problems and collaborate with top researchers.
- Company: Leading firm in quantitative finance with a focus on innovation.
- Benefits: Competitive pay, lunch provided, 30 days leave, and great work-life balance.
- Other info: Dynamic internship with opportunities for growth and collaboration.
- Why this job: Join a world-class team and make an impact in cutting-edge research.
- Qualifications: Current student in machine learning or related field with programming skills.
The predicted salary is between 63000 - 77000 £ per year.
We tackle the most complex problems in quantitative finance, by bringing scientific clarity to financial complexity. From our London HQ, we unite world-class researchers and engineers in an environment that values deep exploration and methodical execution - because the best ideas take time to evolve. Together we’re building a world-class platform to amplify our teams’ most powerful ideas.
As part of our engineering team, you’ll shape the platforms and tools that drive high-impact research - designing systems that scale, accelerate discovery and support innovation across the firm.
We are looking for exceptional machine learning students to join our world-class technology teams for a 12-week summer internship, working alongside quantitative researchers on cutting-edge machine learning problems. As an intern within the Technical Machine Learning team, you will be engaged in a mixture of individual and collaborative work to tackle some of the toughest research questions. You will also use a combination of off-the-shelf tools and custom solutions written from scratch to drive the latest advances in quantitative research.
Key Responsibilities of the role include:
- Implementing ideas from published research papers
- Writing custom libraries to efficiently train models on petabytes of data
- Reducing model training times by hand optimising machine learning operations
- Profiling custom machine learning architectures to identify performance bottlenecks
- Evaluating the latest hardware and software in the machine learning ecosystem
Who are we looking for?
We are looking for interns that will be comfortable working both independently and in small teams on a variety of engineering challenges, with a particular focus on machine learning and scientific computing. The ideal candidate will have the following skills and experience:
- A current undergraduate, master's or PhD student in machine learning or a related discipline
- Strong object-oriented programming skills and experience working with Python, PyTorch and NumPy are desirable
- Experience in one or more advanced optimisation methods, modern ML techniques, HPC, profiling, model inference; you don’t need to have all of the above
- Excellent machine learning reasoning skills, with the ability to develop your own models when standard approaches are insufficient
- Strong communication and collaboration skills, with the ability to work effectively in a team with complementary expertise
Finance experience is not necessary for this role and candidates from non-financial backgrounds are encouraged to apply.
Why join us?
- Highly competitive compensation plus annual discretionary bonus
- Lunch provided (via Just Eat for Business) and dedicated barista bar
- 30 days’ annual leave
- 9% company pension contributions
- Informal dress code and excellent work/life balance
- Comprehensive healthcare and life assurance
- Cycle-to-work scheme
- Monthly company events
Location: London
Machine Learning Engineer Intern in London employer: targetjobs UK
Bloomberg is an exceptional employer, offering a dynamic work environment in London where you can develop your skills in analytics and sales while providing unparalleled customer support to clients across the globe. With a strong emphasis on employee growth, our comprehensive training program equips you with the knowledge needed to excel in the financial markets, while opportunities for career advancement abound within the company. Join us to be part of a culture that values innovation, collaboration, and a commitment to delivering outstanding service.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer Intern in London
✨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 Machine Learning Engineer Intern in London
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 targetjobs UK 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 targetjobs UK
✨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 targetjobs UK.
✨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 targetjobs UK that you’re not just looking for experience, but that you're keen to contribute and grow within the team.
