Quantitative Developer (Python/C++)

Quantitative Developer (Python/C++)

London Full-Time Competitive Salary + Equity

Build technology that solves genuinely hard problems.

We're partnering with an ambitious, venture-backed deep-tech startup that's bringing together exceptional engineers, mathematicians and researchers to tackle some of the most challenging quantitative problems in industry.

This isn't another role maintaining legacy trading systems or optimising existing codebases. You'll be building the core technology from the ground up, developing sophisticated quantitative models and high-performance software that directly powers the company's success.

If you enjoy first-principles thinking, elegant engineering and solving problems that don't have obvious answers, you'll feel right at home.

The Opportunity

You'll join a small, high-calibre engineering team where technical excellence comes first.

There are no rigid silos, endless meetings or layers of bureaucracy. Instead, you'll work closely with experienced software engineers, quantitative researchers and founders to design and build systems that operate at the intersection of mathematics, machine learning and distributed computing.

You'll own meaningful projects from day one, influence technical decisions, and see your work move rapidly from idea to production.

What You'll Be Working On

• Designing and implementing quantitative models in production
• Developing high-performance software in Python and/or C++
• Building scalable data pipelines and distributed systems
• Working with large, complex real-world datasets
• Researching and prototyping new algorithms
• Optimising computational performance and system efficiency
• Collaborating with researchers to turn mathematical ideas into production-grade software
• Contributing to architecture, tooling and engineering best practices
• Helping shape the technical direction of a rapidly growing company

Every project presents new challenges, so curiosity and problem-solving are just as important as technical expertise.

We're Looking For

You'll likely have experience in some of the following:

• Strong software engineering skills in Python and/or C++
• Excellent problem-solving and analytical ability
• A degree (or equivalent experience) in Computer Science, Mathematics, Physics, Engineering or another quantitative discipline
• Experience developing production software
• Knowledge of algorithms, data structures and software design
• Experience working with large datasets or numerical computation
• An interest in optimisation, statistics, machine learning or quantitative modelling

Experience in quantitative finance is welcomed but not essential. We're equally interested in candidates coming from deep-tech, scientific computing, machine learning, robotics, simulation or other computationally intensive environments.

Bonus Experience

Any of the following would be advantageous:

• Quantitative finance
• Machine learning
• Scientific computing
• High-performance computing (HPC)
• Distributed systems
• GPU programming (CUDA)
• Optimisation
• Statistics
• Numerical methods
• Time-series modelling
• Cloud infrastructure
• Docker or Kubernetes

Why This Role?

This is an opportunity to work on problems that are genuinely difficult, alongside people who care deeply about engineering quality and mathematical rigour.

You'll benefit from:

• Working with an exceptionally talented technical team
• Real ownership and autonomy from day one
• A collaborative, low-ego engineering culture
• The chance to influence both technology and product direction
• Fast decision-making and minimal bureaucracy
• Exposure to cutting-edge quantitative techniques
• Competitive salary plus meaningful equity
• A clear path for rapid technical and career progression

Who You'll Thrive Here

This role suits engineers who:

• Love solving complex technical problems
• Enjoy understanding systems from first principles
• Care about writing clean, efficient, maintainable code
• Want to work in an environment where technical ideas are valued
• Are excited by the pace and ownership of an early-stage company
• Prefer building new technology over maintaining legacy systems