Senior ML Engineer - Quantitative Trading Systems

United States Digital Space LLC

Greater London

Hybrid

GBP 120,000 - 160,000

Full time

4 days ago
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Benefits offered by this job

Competitive compensation
Tech talks
Daily catered lunches
Beautiful modern office

Job summary

Group, a technology company applying state-of-the-art AI/ML to finance, seeks a Senior Machine Learning Engineer to translate research into production-grade code and to build data pipelines and modeling infrastructure for quantitative trading.

You will work at the boundary of research and engineering, understanding mathematical concepts, ensuring performance, reliability, and maintainability across systems used by researchers and engineers.

Qualifications

  • Bachelor's degree in Computer Science, Applied Mathematics, Statistics, or related field.
  • 5+ years of professional software engineering experience with strong CS fundamentals.
  • Proficiency in Python; R/C++ is a plus.
  • Experience with numerical and data science libraries (NumPy, Pandas, SciPy, scikit-learn, PyTorch, TensorFlow).
  • Experience building or maintaining ML systems in distributed environments.

Responsibilities

  • Partner with PhD researchers to design and productionize ML models for quantitative trading.
  • Develop and maintain data pipelines, feature engineering, validation, and monitoring.
  • Translate research prototypes into production-ready code with testing.
  • Build extensible tools and frameworks for model development and experimentation.
  • Lead projects, coordinate deployments, and guide junior staff.

Skills

Python proficiency
Distributed computing
Mathematical maturity
Communication skills
Linux development

Education

Bachelor's degree in Computer Science / Applied Mathematics / Statistics

Tools

NumPy
Pandas
SciPy
scikit-learn
PyTorch
TensorFlow

Job description

Group, a technology company applying state-of-the-art AI/ML to finance, seeks a Senior Machine Learning Engineer to translate research into production-grade code and to build data pipelines and modeling infrastructure for quantitative trading.

You will work at the boundary of research and engineering, understanding mathematical concepts, ensuring performance, reliability, and maintainability across systems used by researchers and engineers.

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