Responsibilities
- Architect, design, and implement core components for a Batch and Realtime Streaming platform, including data ingestion pipelines, storage systems, serving layers, and API interfaces
- Ship new features by collaborating across research, legal, trading, finance operations data, and infra teams for trading systems
- Collaborate with ML researchers and data scientists to understand their workflows and design intuitive interfaces (APIs, SDKs, UIs) for seamless feature discovery, access, and reuse
- Ensure data quality, consistency, and lineage for features, building robust mechanisms for versioning, monitoring, and governance
- Optimize data pipelines and storage for high performance, scalability, and reliability, considering both batch and real-time use cases
- Drive adoption of the feature store across teams by producing documentation, onboarding materials, and developer support.
- Mentor junior engineers and contribute to team best practices and technical excellence
Requirements
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field (or equivalent experience)
- 5+ years of software engineering experience, with a strong background in backend systems, distributed computing, or data infrastructure
- Experience in programming languages such as Python, Go, and C++
- Understanding of database technologies (Postgres, MySQL, Cassandra, DynamoDB, SQLite, DuckDB or MongoDB) and experience with APIs (REST/gRPC)
- Strong problem-solving skills, with a focus on delivering high-quality, maintainable, and well-documented solutions
- Excellent communication and collaboration skills; ability to work closely with both engineering and research teams
Preferred Qualifications
- Experience building large-scale data pipelines and storage systems (e.g., Airflow, Spark, etc)
- Exposure to modern Python data science tooling. (pandas, polars, dask, duckdb etc)
- Experience with monitoring and observability tools for distributed systems (e.g., Prometheus, Grafana, ELK Stack)
- Prior experience working with feature stores (e.g., Feast, Hopsworks, or custom solutions) is highly desirable
Top Skills
What We Do
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.