Graduate Machine Learning Engineer

G Research — United Kingdom · Posted ~3 hours ago

Junior Full-time Onsite

Skills

Machine learning Software engineering Research Problem solving Quantitative analysis

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Summary ✨ AI‑Generated

Launch your machine learning engineering career in a research-driven environment focused on difficult problems in quantitative finance. You will collaborate with experienced researchers and engineers, develop scalable platforms and tools, and contribute to cutting-edge machine learning research.

Highlights

Graduate opportunity to work alongside quantitative researchers on challenging machine learning problems, combining research, engineering, collaboration, and large-scale technical problem solving.

Description

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. Take the next step in your career. Start date: Tuesday 31st August 2027 We are looking for exceptional graduate machine learning engineers to work alongside our quantitative researchers on cutting-edge machine learning problems. As a graduate 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 What does the technical machine learning team work on? Implementing ideas from published research papersWriting custom libraries to efficiently train models on petabytes of dataReducing model training times by hand optimising machine learning operationsProfiling custom ML architectures to identify performance bottlenecksEvaluating the latest hardware and software in the machine learning ecosystem Who are we looking for? We are looking for graduates 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 disciplineStrong object-oriented programming skills and experience working with Python, PyTorch and NumPy are desirableExperience in one or more advanced optimisation methods, modern ML techniques, HPC, profiling, model inference; you don’t need to have all of the aboveExcellent machine learning reasoning skills, with the ability to develop your own models when standard approaches are insufficientStrong 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 bonusLunch provided (via Just Eat for Business) and dedicated barista bar30 days’ annual leave9% company pension contributionsInformal dress code and excellent work/life balanceComprehensive healthcare and life assuranceCycle-to-work schemeMonthly company events