# Senior Machine Learning Engineer

**Company:** [The Voleon Group](https://hotfix.jobs/companies/voleon)
**Location:** Remote
**Role:** ML Engineering
**Salary:** $290k – $395k/yr
**Experience:** 5+ years
**Skills:** Python, NumPy, pandas, Scipy, scikit-learn, PyTorch, TensorFlow, Linux, C/C++, R
**Posted:** 2026-05-13

> Partners with researchers to productionize ML models for quantitative trading, builds data pipelines and infrastructure, and leads projects requiring strong Python, math, and ML systems expertise.

## Job Description

## 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**; experience with R and/or C/C++ is a strong plus
- 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 Qualifications
- 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

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