Quantitative Developer

Manifold Technologies is a quantitative trading firm building systems that curve with the market’s geometry. We don’t chase trends—we curve the field until structure reveals itself. Most systems collapse when curvature shifts. Ours adapts because it is built from within. Bayesian inference and differential geometry aren’t frameworks we borrow—they are the native language of our architecture.

Please read the information in this job post thoroughly to understand exactly what is expected of potential candidates.

We’re looking for a Quantitative Developer Intern to support the engineering and research teams in the development of our internal infrastructure. This role involves writing Python code to implement, test, and integrate modules that support our geometric signal logic and execution pipeline. You’ll work on clearly scoped technical problems that matter—and contribute to a system that behaves differently than anything built from statistical shortcuts or backtest tuning.

The ideal candidate is pursuing or has recently completed a degree in computer science, mathematics, or a related field at a top-tier institution (e.g., Stanford, MIT, Berkeley, CMU) with a GPA of at least 3.9. They should have a strong foundation in linear algebra, probability, and machine learning, and be comfortable reasoning from structure, not just applying libraries.

About You

You’re pursuing (or have recently completed) a degree in computer science, mathematics, or a related field at a top institution, with a strong academic track record

You’re comfortable working from first principles, and can reason through systems where intuition matters more than templates

You’re a strong programmer, particularly in Python, and can translate ideas into code that runs cleanly and predictably

You’re open-minded and rigorous—willing to implement ideas you may not have invented, but capable of holding their structure through execution

You’re curious about trading systems, but more interested in how they survive tension than how they chase noise

Responsibilities

Write clean, maintainable Python to support modules used in signal generation, evaluation, and execution

Implement mathematical logic—often geometric or probabilistic—under the guidance of the research team

Work on internal simulation tools, data pipelines, or test frameworks depending on experience and team needs

Participate in field-aligned discussions around implementation tradeoffs and experimental structure

Learn the logic of the system—not just how it works, but how and why it holds

Compensation

The weekly base pay will range from $3,000-$4,500 with actual compensation for successful candidates carefully determined based on a number of factors, including their skills, qualifications, and experience. Additional benefits—such as health coverage, wellness stipends, or retirement contributions—may be offered depending on the final structure of the offer. xklufbp

Manifold Technologies is an Equal Opportunity Employer.