At a Glance
- Tasks: Develop and deploy machine learning models on high-frequency market data.
- Company: Join a top-tier global hedge fund committed to tech and data innovations.
- Benefits: Competitive salary, dynamic work environment, and opportunities for professional growth.
- Other info: Collaborative culture with excellent career advancement opportunities.
- Why this job: Make an impact in finance by leveraging cutting-edge technology and data.
- Qualifications: Master’s or PhD in a quantitative field with 3+ years of relevant experience.
The predicted salary is between 63000 - 77000 £ per year.
Millennium is a top tier global hedge fund with a strong commitment to leveraging market innovations in technology and data to deliver high-quality returns.
A collaborative and entrepreneurial systematic macro pod is seeking an experienced Quantitative Developer with a machine learning focus. You will develop and deploy machine learning models on high-frequency market data, and build the research and compute infrastructure behind them.
Location: London
Principal Responsibilities:
- Design, train and productionize large-scale machine learning models across both classical and deep learning approaches, applied to high-frequency data.
- Enhance and optimize the pod’s end-to-end machine learning pipeline, from large-scale data processing and distributed computation to scalable parameter search and validation.
- Contribute to improving the speed, scalability, and reliability of the pod’s wider signal development environment, ensuring consistent and efficient migration from research to production.
- Partner with broader technology teams to make effective use of shared internal platforms and services.
Qualifications:
- Master’s or PhD/Post doctorate in Computer Science, Mathematics, Statistics, Engineering, Physics, or a related quantitative discipline, from a leading institution.
Preferred Technical Skills:
- 3+ years of professional experience in software engineering, quantitative development, or a related computational role.
- Experience developing and validating machine learning models on large, complex datasets, across 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 — parallelism, distributed compute, and native acceleration such as Python or C++ bindings.
- Familiarity with C++ is a strong plus, alongside the software engineering fundamentals to pick it up quickly.
- Experience building data-intensive tools, research workflows, or model development infrastructure.
- Strong Linux development experience.
- Experience building agentic AI systems — tool use, orchestration, and evaluation.
High Valued Experience:
- Experience with backtesting and awareness of common research pitfalls such as overfitting, lookahead bias, and survivorship bias.
- Understanding of systematic trading strategies and quantitative research workflows.
- Knowledge of market microstructure.
- Experience supporting production research workflows or model deployment in a front-office environment.
Quantitative Developer, Research & ML Engineering, Systematic Macro in London employer: United States Digital Space LLC
United States Digital Space LLC is an exceptional employer, offering a dynamic work culture that prioritises innovation and collaboration in the heart of Greater London. With a strong focus on employee well-being and flexible work options, we provide ample opportunities for professional growth and development, making it an ideal environment for those looking to make a meaningful impact in the field of AI-enabled SaaS engineering.
Contact Details:
United States Digital Space LLC Recruitment Team
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