Machine Learning Engineer

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.

We are looking for exceptional machine learning engineers to work alongside our quantitative researchers on cutting-edge machine learning problems.

As a member of the Core Technical Machine Learning team, you will be engaged in a mixture of individual and collaborative work to tackle some of the toughest research questions.

In this role, you will use a combination of off-the-shelf tools and custom solutions written from scratch to drive the latest advances in quantitative research.

Past projects have included:

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• Implementing ideas from a recently published research paper
  
• Writing custom libraries for efficiently training on petabytes of data
  
• Reducing model training times by hand optimising machine learning operations
  
• Profiling custom ML architectures to identify performance bottlenecks
  
• Evaluating the latest hardware and software in the machine learning ecosystem
  

Candidates 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:

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• Either a post-graduate degree in machine learning or a related discipline, or commercial experience working on machine learning models at scale. We will also consider exceptional candidates with a proven record of success in online data science competitions, such as Kaggle
  
• 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 ML reasoning and communication skills are crucial: off-the-shelf methods don’t always work on our data so you will need to understand how to develop your own models in a collaborative environment working in a team with complementary skills
  

Finance experience is not necessary for this role and candidates from non-financial backgrounds are encouraged to apply.

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• Highly competitive compensation plus annual discretionary bonus
  
• Lunch provided (viaJust Eat for Business) and dedicated barista bar
  
• 35 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