The Voleon Group

Senior / Staff Software Engineer - Batch and Realtime Streaming

Berkeley, California, United States

Not SpecifiedCompensation
Senior (5 to 8 years), Expert & Leadership (9+ years)Experience Level
Full TimeJob Type
UnknownVisa
Biotechnology, Finance, Artificial Intelligence, AI & Machine Learning, Asset ManagementIndustries

Requirements

Candidates must possess a Bachelor's or Master's degree in Computer Science, Engineering, or a related field, or equivalent experience, along with 5+ years of software engineering experience focused on backend systems, distributed computing, or data infrastructure. Proficiency in programming languages such as Python, Go, and C++, understanding of database technologies (e.g., Postgres, MySQL, Cassandra, DynamoDB, SQLite, DuckDB, MongoDB), and experience with APIs (REST/gRPC) are essential. Strong problem-solving skills, a focus on delivering high-quality, maintainable, and well-documented solutions, and excellent communication and collaboration skills are also required. Preferred qualifications include experience building large-scale data pipelines and storage systems (e.g., Airflow, Spark) and exposure to modern Python data science tooling (pandas, polars, dask, duckdb).

Responsibilities

The Senior/Staff Software Engineer will architect, design, and implement core components for a Batch and Realtime Streaming platform, including data ingestion pipelines, storage systems, serving layers, and API interfaces. They will ship new features by collaborating across research, legal, trading, finance operations data, and infra teams for trading systems. The engineer will also collaborate with ML researchers and data scientists to understand their workflows and design intuitive interfaces for seamless feature discovery, access, and reuse. Key duties include ensuring data quality, consistency, and lineage for features, building robust mechanisms for versioning, monitoring, and governance, and optimizing data pipelines and storage for high performance, scalability, and reliability. Additionally, they will drive adoption of the feature store across teams by producing documentation, onboarding materials, and developer support, and mentor junior engineers while contributing to team best practices and technical excellence.

Skills

AI
Machine Learning
Batch Processing
Realtime Streaming
Data Architecture
Software Development
High-Performance Interfaces
Feature Engineering
Quantitative Finance

The Voleon Group

Investment management using machine learning algorithms

About The Voleon Group

Voleon focuses on investment management by utilizing machine learning to analyze financial market trends. The firm uses advanced statistical models to process large datasets and identify patterns that inform investment decisions, setting it apart from traditional methods that rely on human intuition. Voleon serves institutional clients and operates on a performance-based fee structure, aligning its interests with those of its clients. The company's goal is to provide data-driven insights that optimize investment returns while adapting to changing market conditions.

Berkeley, CaliforniaHeadquarters
2007Year Founded
VENTURE_UNKNOWNCompany Stage
Quantitative Finance, Financial ServicesIndustries
51-200Employees

Benefits

Health Insurance
Dental Insurance
Vision Insurance
Life Insurance
Paid Vacation
Paid Sick Leave
401(k) Retirement Plan
401(k) Company Match

Risks

Competition from other quantitative hedge funds may erode Voleon's market share.
Regulatory scrutiny on AI use in finance could increase compliance costs for Voleon.
Data quality issues could lead to inaccurate predictions and financial losses for Voleon.

Differentiation

Voleon uses machine learning for data-driven financial market predictions.
The firm serves institutional clients with a focus on scalability and risk management.
Voleon's academic approach emphasizes intellectual rigor and continuous learning.

Upsides

Increased interest in ESG investing offers new opportunities for Voleon's models.
Alternative data sources enhance predictive models for quantitative hedge funds like Voleon.
Cloud computing enables efficient scaling of Voleon's data processing capabilities.

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