Software Engineer Intern - (Summer 2026) at The Voleon Group

Berkeley, California, United States

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Not SpecifiedCompensation

InternshipExperience Level

InternshipJob Type

UnknownVisa

Finance, Quantitative TradingIndustries

Requirements

Availability to work a full-time internship during the summer, fall, or winter of 2026
Expected to graduate in 2027
Hands-on experience writing code: You have built something significant. You understand how to write modular, maintainable, well-organized, and thoughtfully structured code
Mastery of Computer Science fundamentals
Modern software practices: You are comfortable using Linux, git, and mainstream databases. You are familiar with cloud infrastructure
You are incredibly good at at least one thing
You are eager to work in diverse teams

Responsibilities

Designing complex systems
Take on a lot of responsibility very quickly. You will “own” your work (passionately)

Skills

Linux

Git

Databases

Cloud Infrastructure

Machine Learning

Distributed Systems

Real-time Systems

Software Design

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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