Senior Machine Learning Engineer
$290 K - $395 K
Apply (opens in a new tab)Senior Machine Learning Engineer
Posted 51 days ago
SENIORITY
Senior
SALARY
$290 K - $395 K
About the role
- 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
- 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
- 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"Friends of Voleon" Candidate Referral Program
Before you apply
Applying takes about a minute. These four things decide how fast it moves after that.
Your profile is current
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Two examples you can talk through
Not a portfolio — just two pieces of work where you can explain the decisions and what you'd change.
A number in mind
What you're on now and what would make you move. We negotiate better when we know both.
Your notice period
Employers plan around it, and it's the question that stalls offers most often.
Once you apply, someone reads it and calls you before anything reaches the employer — usually within two working days.
