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Our Engineering teams partner with our researchers, design real-time platforms and process massive datasets at speed and scale.

We solve some of the world’s most complex financial problems; without our engineers, we couldn’t. The size and breadth of our Engineering function reflects the critical work they do.

Quantitative Engineering

Our quantitative engineers are the enablers of our success. They work side-by-side with our researchers at the bleeding-edge, with near-infinite compute power at their fingertips, to achieve our aim: predicting the future.

We have specialist teams in machine learning, data engineering and high-performance, low-latency systems.

Infrastructure Engineering

We deliver a complex infrastructure that stores and processes phenomenal amounts of data daily.

We constantly seek out ways to automate and innovate, from exploring cloud technologies and flash scalable storage to grid computing and adopting an infrastructure-as-code mindset – anything that gives us the research edge.

Our Size and Scale

We have access to around 300 Petabytes of storage. That's enough to store every piece of data you would generate over 100 lifetimes.
Kafka clusters in production handle 90 billion events and messages per day. That's almost twice as many messages as are sent on WhatsApp globally each day.
Systems we have developed are used to collect and ingest 80TB of log data per day. That's around 8 times all of the works in the Library of Congress, every day.

What Our People Say

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Simon Technical Signals Engineering Manager

"I continue to be blown away by the quality of the people I get to work with here: G-Research thrives because of its team culture and we’ve hired carefully to make sure everyone is both exceptionally smart and great to work with."

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Mario FPGA Manager

"While some people might think working in finance may not be too exciting, at G-Research, it is, especially if you see it as a problem to solve. How do we solve this algorithm? How do we get faster? This is why I think people are really excited to work at G-Research."

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Alexander Software Engineering Manager

"I've felt very lucky to work with teams of people across the business who are generous with their time, knowledge and ideas as we collaborate to continuously build and rebuild complex systems with lots of moving parts."

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Mia Infrastructure Development Software Engineer

"What I appreciate most about working in G-Research is the supportive and knowledgeable environment. Everyone is incredibly helpful and patient, which ensures there’s a good balance between being challenged and your workload."

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Dexter SOFTWARE ENGINEER

"Work culture is an important aspect for me, so when I was contacted by G-Research I discovered a company where I could grow as a developer, whilst feeling like the company valued me as a person, not just a code monkey."

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Neil Corporate Infrastructure and Security Engineering Manager

"My favourite part of working for G-Research is that Technology is at the heart of everything we do at the company, driving the business forward and enabling us to stay ahead of the competition."

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Owen SOFTWARE ENGINEER

"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."

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Sokratis SOFTWARE ENGINEER

"My favourite part of working at G-Research is the people, from my colleagues to our customers. The culture is great and encourages collaboration, which makes it easier for everyone to work together. It’s also great to be able to use the latest tech, like Kubernetes and Kafka."

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Ross Cloud Engineering Manager

"My favourite thing about working at G-Research is the people. G-Research strives to hire not only the brightest minds, but good people, which in turn creates a brilliant collegiate and social atmosphere at the company."

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Assessment Process for Engineering

We look for outstanding engineers with varied experience depending on the role and team you’re interested in. Learn more about our assessment process.

Online Application

Our assessment process kicks off with our Talent Acquisition team, who will review your application and assess your fit for the role.

Stage One: Technical Interview

You will meet with a team member – or take a remote test – where your technical abilities will be put to the test.

Stage Two: Behavioural Interview

We will set aside technical skills and focus on you.

Stage Three: Further Technical Interviews

Here, we will take a deeper dive into your technical skills and competencies.

Stage Four: Management Interviews

The final stage of our interview process is where you will meet members of your team, your future manager, and functional leadership.

Our Opportunities

Looking to make an impact at one of the world’s leading quantitative research and technology firms? See our open roles and apply now.

Latest news

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Building Modern, Resilient and Reliant Infrastructure
  • 15 Jul 2024

In this video, Philip Bullock, US IaaS Lead, shares insights into our approach to infrastructure innovation. He delves into the immense compute power that underpins G-Research and explains how we ensure we stay at the cutting edge of technology and finance.

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Celebrating Our New Dallas Home
  • 11 Jul 2024

Our new office at One Victory Commons, Dallas, exemplifies our commitment to excellence, providing a state-of-the-art setting that truly reflects the cutting-edge work we do.

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An interview with Michael Kagan (CTO at NVIDIA)
  • 02 Jul 2024

We spoke to Michael Kagan, CTO at NVIDIA, in an exclusive interview shot ahead of his keynote talk at the G-Research Distinguished Speaker Symposium.

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Latest events

  • Quantitative Engineering
  • Software Engineering

Jobs for Mathematicians Fair (University of Oxford)

19 Nov 2024 Mathematical Institute, Radcliffe Observatory, Andrew Wiles Building, Woodstock Road, Oxford, OX2 6GG,
  • Quantitative Engineering
  • Software Engineering

University of Cambridge: Maths and Quants Fair

30 Oct 2024 Student Services Centre, New Museum Site, Bene't St, Cambridge CB2 3PT
  • Quantitative Engineering
  • Software Engineering

The SEC Engineering Career Fair

04 Sep 2024 Legends Event Center, 2533 Midtown Pk Blvd, Bryan, TX 77801, United States

Other teams

Quantitative Research & Machine Learning

We find patterns in noisy, real-world datasets to predict movement in financial markets.

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Technology Innovation Group

We identify, test and on-board the latest tech, enabling our researchers and engineers to keep innovating.

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Open-Source Software

We partner with and invest in the open-source community.

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