Machine learning engineer for quantitative trading in London

Machine learning engineer for quantitative trading in London

London Full-Time 72000 - 88000 £ / year (est.) On-site
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At a Glance

  • Tasks: Collaborate with PhD researchers to develop cutting-edge machine learning models for quantitative trading.
  • Company: Join Voleon, a leading tech company in AI-driven finance.
  • Benefits: Enjoy competitive pay, daily catered lunches, and a vibrant office culture.
  • Other info: Dynamic environment with opportunities for growth and collaboration.
  • Why this job: Make a real impact in finance using state-of-the-art AI and ML technologies.
  • Qualifications: Bachelor's degree in a quantitative field and 5+ years of software engineering experience.

The predicted salary is between 72000 - 88000 £ per year.

Voleon is a technology company that applies state-of-the-art AI and machine learning techniques to real-world problems in finance. For nearly two decades, we have led our industry and worked at the frontier of applying AI/ML to investment management. We have become a multibillion-dollar asset manager, and we have ambitious goals for the future.

As a Senior Machine Learning Engineer on one of Voleon's Research teams, you will partner directly with research staff to advance our quantitative trading strategies.

Responsibilities:

  • Partner with PhD researchers to design, implement, and productize machine learning models that drive quantitative trading strategies.
  • Develop and maintain complex data pipelines, including data ingestion, feature engineering, validation, and quality monitoring.
  • Translate research prototypes and novel ideas into performant, well-tested, production-ready code.
  • Build extensible tools and frameworks that accelerate the model development and experimentation lifecycle.
  • Supervise, understand, and remediate subtle data quality issues across both research and production environments.
  • Proactively lead projects from requirements through delivery, making autonomous decisions about scope, dependencies, and trade-offs, with an emphasis on long-term maintainability.
  • Coordinate and contribute to deployment efforts while guiding junior engineers and researchers; align with research and engineering stakeholders on ownership, execution, and prioritization.
  • Foster engineering consistency, standards, and best practices within Research.

Requirements:

  • Bachelor's degree (or higher) in Computer Science, Applied Mathematics, Statistics, or a related quantitative field.
  • 5+ years of professional software engineering experience, with strong CS fundamentals (data structures, algorithms, systems design).
  • Demonstrated mathematical maturity — comfort with the concepts and notation used in statistics, linear algebra, optimization, and probability.
  • Deep proficiency in Python.
  • Extensive experience with numerical and data science libraries (e.g., NumPy, Pandas, SciPy, scikit-learn, PyTorch, TensorFlow, or similar).
  • Proven experience building or maintaining machine learning systems in a distributed computing environment.
  • Proficiency developing in a Linux environment with attention to performance, correctness, and reproducibility.
  • Exceptional attention to detail, particularly when working with imperfect or heterogeneous data.
  • Strong verbal and written communication skills, and the ability to collaborate effectively with researchers whose primary expertise is not software engineering.

Preferred:

  • Experience with R and/or C/C++ is a strong plus.
  • Experience with experiment management, model evaluation pipelines, or ML workflow orchestration.
  • Familiarity with modern ML/AI infrastructure patterns (model serving, feature stores, distributed training).
  • Experience with performance profiling and optimization of numerical or modeling code.
  • Prior exposure to financial data, time-series analysis, or quantitative research environments.

Conditions:

In addition to our enriching and collegial working environment, we offer highly competitive compensation and benefits packages, technology talks by our experts, a beautiful modern office, daily catered lunches, and more.

Machine learning engineer for quantitative trading in London employer: The Voleon Group

Voleon is an exceptional employer that fosters a collaborative and innovative work culture, where Site Reliability Engineers can thrive alongside experts in AI and finance. With competitive compensation, daily catered lunches, and opportunities for professional growth, employees are empowered to make impactful contributions in a modern office environment. The diverse backgrounds of our team members create a unique atmosphere that celebrates creativity and success, making Voleon a truly rewarding place to work.

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Contact Details:

The Voleon Group Recruitment Team

StudySmarter Expert Advice🤫

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We think you need these skills to ace Machine learning engineer for quantitative trading in London

Machine Learning
Data Pipelines
Feature Engineering
Python
NumPy
Pandas
SciPy

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