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Senior Machine Learning Engineer

Role overview

Qualifications

  • 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)
  • Deep proficiency in Python; experience with R and/or C/C++ is a strong plus
  • Demonstrated mathematical maturity β€” comfort with the concepts and notation used in statistics, linear algebra, optimization, and probability

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

About the company

The Voleon Group logo

The Voleon Group

Investment Management

Founded in 2007 by two machine learning scientists, The Voleon Group is a quantitative hedge fund headquartered in Berkeley, CA. We are committed to solving large-scale financial prediction problems with statistical machine learning. The Voleon Group combines an academic research culture with an emphasis on scalable architectures to deliver technology at the forefront of investment management. Many of our employees hold doctorates in statistics, computer science, and mathematics, among other quantitative disciplines. Voleon's CEO holds a Ph.D. in Computer Science from Stanford and previously founded and led a successful technology startup. Our Chief Investment Officer and Head of Research is Statistics faculty at UC Berkeley, where he earned his Ph.D. Voleon prides itself on cultivating an office environment that fosters creativity, collaboration, and open thinking. We are committed to excellence in all aspects of our research and operations, while maintaining a culture of intellectual curiosity and flexibility. The Voleon Group is an Equal Opportunity employer. Applicants are considered without regard to race, color, religion, creed, national origin, age, sex, gender, marital status, sexual orientation and identity, genetic information, veteran status, citizenship, or any other factors prohibited by local, state, or federal law.

Company details

Company typeSME
IndustryInvestment Management
Company size51 - 200

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Job description

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

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, catered lunches, and more.

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. You will translate novel research ideas into production-quality code, build and maintain the data pipelines and modeling infrastructure that underpin our strategies, and apply your own strong mathematical intuition to solve open-ended technical challenges.

This role lives at the boundary of research and engineering. You will be expected to understand the statistical and mathematical concepts your research partners work with, contribute meaningfully to technical discussions about model design and evaluation, and ensure that the resulting systems are performant, reliable, and maintainable. You will work at the intersection of Computer Science, Mathematics, and Statistics β€” building high-performance tools that enable world-class research while maintaining a high engineering standard.

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 β€” 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

β€œFriends of Voleon” Candidate Referral Program

If you have a great candidate in mind for this role and would like to have the potential to earn $15,000 if your referred candidate is successfully hired and employed by The Voleon Group, please use this form to submit your referral. For more details regarding eligibility, terms and conditions please make sure to review the Voleon Referral Bonus Program.

 

Equal Opportunity Employer

The Voleon Group is an Equal Opportunity employer. Applicants are considered without regard to race, color, religion, creed, national origin, age, sex, gender, marital status, sexual orientation and identity, genetic information, veteran status, citizenship, or any other factors prohibited by local, state, or federal law.

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Marcus Rivera

Chief Revenue Officer

m.rivera@company.com
linkedin.com/in/marcusrivera
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