Whether you join us in quantitative research, machine learning or engineering, you’ll work on real problems, contribute to live projects and gain the experience needed to thrive in a full-time role. Here’s where your journey can begin
Internships at G-Research
What you need to knowOur internships give you a platform to prove you belong amongst the best. If you’re ready to learn fast, think bigger and work with minds operating at unrivalled levels, you’re in the right place. Learn more about G-Research internships here.
Why an internship at G-Research?
An internship at G-Research isn’t a preview of real work – it is real work. You’ll join world-class researchers and engineers on problems that genuinely matter. With access to massive datasets, powerful compute infrastructure and a culture built on curiosity, you’ll learn faster here than anywhere else.
You’ll be paired with senior mentors, surrounded by brilliant people and given the freedom to explore ideas that could become the foundations of future research. Once you’ve experienced this level of challenge, impact and collaboration, nothing else compares – which is why this is an experience that doesn’t just pad out the CV, it accelerates your career.
Types of internships we offer
ML & quant research internships
Our internships place you at the intersection of research and engineering, working on ML problems that operate at a scale many can’t match. Expect to train models on specialised datasets, experiment with cutting-edge architectures, and collaborate with ML engineers, platform teams and quantitative researchers.
It’s hands-on, high-impact and designed for those who want to see their ideas move from notebook to production. For aspiring researchers, this is one of the fastest ways to level up.
Engineering internship
Over 12 or 24 weeks, you’ll be creating the infrastructure that makes G-Research’s research possible: building tools our teams will actually use, scaling infrastructure that handles huge workloads and improving reliability in systems where downtime means missed market opportunities.
If you want engineering work that matters from day one, where performance and scale aren’t buzzwords but requirements, our engineering internship is your arena.
Corporate internships
Most corporate internships give you one function and a lot of coffee runs. Ours give you exposure across departments and the responsibility to make an impact. For instance, our 12-month sandwich HR internship embeds you across People Operations, Talent Acquisition and Marketing, not as an observer, but as a working contributor with real responsibility.
One day you might be supporting core HR processes, the next helping to deliver recruitment campaigns that bring exceptional talent into the firm. By the end of the year, you’ll understand how a high-performing research and technology firm actually operates from the inside – the people decisions, the processes, the priorities that keep everything running.
What our interns say
"My internship was a hugely valuable experience that sharpened my skills and gave me a new perspective on building models with real-world impact."
"One of the things that has truly stood out to me is the collaborative and welcoming culture. I hadn’t expected such a supportive environment but it’s been one of the main reasons I’ve enjoyed working here from day one."
"Before G-Research I’d completed internships at a few companies whilst studying Computer Science at the University of York. Since joining, I’ve progressed from an intern to a graduate to an engineer, having worked on systems and technology core to the business my entire time."
"What I like the most about my job is it’s super open. I’m able to work with a lot of folks from other teams, too, such as working closely with engineers and other quantitative researchers."
A day in the life of a G-Research intern
Life as a G-Research intern isn’t about sitting on the sidelines. From day one, you’ll be immersed in challenging research problems and here’s what that could look like.
Start with real research
From the get-go, you’ll be analysing data that feed live strategies, exploring new modelling ideas that could become production systems, testing hypotheses that our researchers are actively debating or reviewing results from overnight runs. The data is real. The stakes are real. The problems you’re solving aren’t constructed for educational purposes, they’re the ones that we actually need solved.
Work closely with your mentor
Every intern works with a senior researcher or engineer who’s invested in your development, not just supervising, but actively shaping how you think. Expect regular one-on-ones where your mentor probes your reasoning, whiteboarding sessions where you work through problems together and candid feedback that’s constructive but never sugar-coated.
They’ll push you harder than you’re used to, challenge assumptions you didn’t know you were making and help you develop the instincts that separate good engineers or researchers from exceptional ones.
Collaborate across disciplines
You’re not siloed with other interns doing parallel projects, you’re gaining exposure to how our different disciplines combine.
You’re working alongside quantitative researchers who’ll critique your statistical approach, ML engineers who’ll help optimise your models for production, platform engineers who’ll show you how to scale your solution and other researchers who’ll pressure-test your ideas in ways that make them stronger.
Build, code, iterate
Most of your time is hands-on technical work: coding models, running experiments, cleaning and shaping datasets, evaluating results and refining methods that actually work at G-Research level rigour. You’ll have access to the datasets, tooling and computational resources needed to explore challenging research questions during your internship.
Learn, explore and push ideas further
The intellectual environment is relentless in the best way. You’re attending internal seminars where researchers present cutting-edge work, absorbing academic papers that haven’t been widely adopted yet, and brainstorming new research directions with your team. You’ll test approaches that seem promising but might fail spectacularly, and that’s encouraged, not penalised. The willingness to explore unconventional ideas is how breakthroughs happen.
End the day with progress you can see
By the end of your internship, you won’t just understand G-Research – you’ll have contributed to it. Your work doesn’t vanish into a folder, it can feed into our actual research, used by people who don’t care that you were an intern. They care that it works.
What happens after the internship?
For many interns, this is just the beginning. Top performers are frequently offered full-time positions – often before the internship ends. Because you’re working on real research problems, your impact is easy to see, and your potential becomes clear fast.
Once you join full-time, you step straight into meaningful work. You’ll take on bigger projects, explore new research directions, deepen your technical expertise and collaborate even more closely with senior researchers, ML specialists and engineers. Your development is supported with mentorship, workshops and access to continuous learning programmes like ML College. From there, the path is yours to define.
How to apply for an internship
Who we’re looking for
For graduate and early-career roles, we typically require:
- Either a PhD level study or at least a post-graduate degree in a highly technical or quantitative topic such as: Mathematics, statistics, ML/AI, physics, computer science, or engineering. For engineering internships, a 2:1 or higher in a relevant field.
- Serious coding ability: Python or C++ proficiency, experience with modern ML frameworks where applicable.
- Research credentials: Publications, impactful academic work or demonstrable contribution to your field help you stand out.
- Intellectual drive: You don’t just complete assignments, you pursue questions that no one asked you to answer.
If you have an obsession with solving complex problems and you’re eager to get involved, we’d love to hear from you.
The application journey
Our 10, 12 and 24-week intern programmes typically follow this process:
- Online application: Tell us who you are and what you’ve done
- Online assessment and triage
- Meet your potential mentors: Conversations with researchers or engineers you’d work alongside
- Meet the leadership team
- Formal internship offer, where you join a cohort that’s genuinely exceptional
What makes candidates stand out
Meeting requirements gets you considered. Standing out requires showing us how your mind actually works.
- Show curiosity that led somewhere, walk us through experiments you designed, ideas you tested or problems you explored purely because you wanted to understand them.
- Go deep on one thing rather than broad on everything. Pick a research problem you’ve genuinely wrestled with and explain the challenges, successes and the process you took.
- Demonstrate you’ve contributed something. Publications, presentations, open-source contributions, or any artifact that shows you moved knowledge forward, even incrementally.
- Prove you build things independently. Personal ML projects, quantitative experiments, simulations,
- Kaggle competitions, technical blog posts, GitHub repositories. Show us work you pursued because it fascinated you, not because it was assigned.
Frequently asked questions
For research roles, typically yes. For engineering internships, a 2:1 or higher in a relevant discipline is sufficient.
Many do, but it’s not automatic. If you demonstrate you can operate at G-Research-level and there’s mutual fit, the path from intern to full-time is clear and well-trodden.
Yes, our internships are highly competitive and fully paid. In addition to salary, we also provide accommodation for our research internships, ensuring you can focus entirely on the work, the learning and the experience.
Duration and depth. All programmes involve real work with genuine impact. Longer programmes allow you to see projects through multiple iterations and gain deeper exposure across teams.
You’ll complete an online assessment, then progress to interviews with potential mentors and leadership. The process is rigorous but transparent, so that you understand the internship.
You’ll complete an online assessment that tests how you approach problems, then move to interviews with the researchers or engineers you’d work alongside, followed by conversations with senior leadership. It’s rigorous but straightforward, we want you to understand what the internship entails and get a genuine evaluation of fit from both sides.
Collaborative, friendly and genuinely helpful. People challenge your ideas in design reviews, then help you improve them. No politics, no ego, no expectation that you prove yourself through overworking hours.
Yes, for the right candidates. If you need sponsorship, mention it in your application, we offer various bespoke relocation packages for our candidates.
Smart-casual. No suits required, just be comfortable and presentable.
All internships take place at our London HQ in Soho Place – right at the intersection of Oxford Street and Tottenham Court Road.