An established, globally recognised investment firm is seeking an experienced Quantitative Developer with a focus on Machine Learning to join a collaborative and entrepreneurial investment team.
The successful candidate will develop and deploy machine learning models using high-frequency financial data, while building and enhancing the research and computational infrastructure that supports them.
Working closely with senior investment professionals, you will translate advanced machine learning research into production-ready models and signals. The role will also involve enhancing the wider research infrastructure, including distributed computation, large-scale parameter optimisation, and efficient workflows from research through to production.
- Design, train and productionise large-scale machine learning models, spanning both classical and deep learning approaches.
- Enhance and optimise end-to-end machine learning pipelines, from large-scale data processing and distributed computation to scalable parameter search and model validation.
- Improve the speed, scalability and reliability of research and signal development environments, ensuring efficient migration from research into production.
- Collaborate with broader technology teams to leverage shared internal platforms, tools and services effectively.
Qualifications
- Master's degree, PhD or postdoctoral qualification in Computer Science, Mathematics, Statistics, Engineering, Physics or a related quantitative discipline from a leading academic institution.
Preferred Technical Skills
- Experience developing and validating machine learning models on large, complex datasets, covering both classical and deep learning approaches, in industry or academia.
- Experience building distributed computing systems for machine learning applications.
- Strong Python programming skills beyond the standard research stack, including parallelism, distributed computing and native acceleration (e.g. Python or C++ bindings).
- Familiarity with C++ is a strong advantage, alongside the software engineering fundamentals to develop proficiency quickly.
- Experience building agentic AI systems, including tool use, orchestration and evaluation.
- Experience with backtesting and an understanding of common quantitative research pitfalls, including overfitting, lookahead bias and survivorship bias.
- Understanding of systematic investment strategies and quantitative research workflows.
- Experience supporting production research workflows or model deployment within a front-office environment.
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Quantitative Developer employer: Upward Trend
Upward Trend in London is an exceptional employer, offering a dynamic work culture that fosters collaboration and innovation within the finance sector. Employees benefit from comprehensive professional development opportunities, competitive compensation packages, and the chance to work on exciting projects in the Emerging Markets space, particularly in the Telco and Consumer sectors. With a focus on employee growth and a supportive environment, this role provides a unique opportunity to make a significant impact while advancing your career.
