Senior Machine Learning Engineer
The Voleon Group2 days ago
London, United KingdomSenior
Responsibilities
- Partner with PhD researchers to design, implement, and productize machine learning models for quantitative trading strategies.
- Develop and maintain data pipelines covering ingestion, feature engineering, validation, and quality monitoring.
- Translate research prototypes into performant, well-tested, production-ready code.
- Build tools and frameworks that accelerate model development and experimentation.
- Identify and remediate subtle data-quality issues across research and production environments.
- Lead projects from requirements through delivery and make autonomous scope, dependency, and trade-off decisions.
- Coordinate deployment efforts, guide junior engineers and researchers, and align stakeholders on ownership and prioritization.
- Promote engineering consistency, standards, and best practices within the Research organization.
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 data structures, algorithms, and systems design fundamentals.
- Mathematical maturity in statistics, linear algebra, optimization, and probability.
- Deep proficiency in Python; experience with R and/or C/C++ is a strong plus.
- Extensive experience with numerical and data science libraries such as NumPy, Pandas, SciPy, scikit-learn, PyTorch, or TensorFlow.
- Experience building or maintaining machine learning systems in a distributed computing environment.
- Proficiency developing in Linux with attention to performance, correctness, and reproducibility.
- Strong attention to detail when working with imperfect or heterogeneous data.
- Strong verbal and written communication skills and effective collaboration with research teams.
- Preferred qualifications include experiment management, model evaluation pipelines, ML workflow orchestration, model serving, feature stores, distributed training, performance profiling, numerical optimization, financial data, time-series analysis, or quantitative research experience.
Benefits
- Competitive compensation and benefits packages.
- Technology talks by company experts.
- Beautiful modern office.
- Daily catered lunches.
Categories
Data EngineeringML Engineering