Quantitative Developer Internship (Winter 2026)

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Arena, Town of Middletown, NY, USA
In-Office
Artificial Intelligence • Fintech • Software • Analytics • Financial Services
The Role
Quantitative Developer Intern – Trading Systems

Company: Blockhouse
Location: Remote (US time zones preferred; NYC in person if possible)
Type: Internship (Start ASAP, through end of May. Return offers granted to high performers)

About Blockhouse

Blockhouse is building an integrated systematic investment platform that designs, deploys, and operates fully automated trading strategies across liquid global markets. Our focus is on high-performance execution, robust research infrastructure, and production-grade trading systems that support systematic strategies end to end.

We are actively building the core infrastructure for HFT-style strategies: low-latency execution services, real-time market data pipelines, simulation and backtesting engines, and the operational systems required to run strategies at scale. This is not a research-only environment — the systems we build are used directly in live trading.

We’re looking for engineers who want to work close to the metal, understand the realities of production trading systems, and are excited to help build the foundation of a modern systematic investment platform.

Role Overview

This is a hands-on trading systems and infrastructure role focused on building and optimizing components that sit directly in the trading path. You’ll work closely with senior quant developers and researchers on low-latency services, messaging systems, and execution logic.

This role is ideal for someone who enjoys modern C++, is comfortable in UNIX environments, and wants real exposure to how systematic strategies are run in production.

What You’ll Do
  • Build and optimize performance-critical components in modern C++ (C++17+)

  • Develop and maintain event-driven execution systems and real-time services

  • Work with message buses to handle market data and order flow

  • Debug and profile low-latency systems using GDB and standard UNIX tooling

  • Implement and test trading simulations and backtesting components

  • Collaborate with quant researchers to translate strategy logic into production-ready systems

  • Improve system reliability, observability, and fault tolerance

  • Deploy and operate services in UNIX/Linux environments (AWS exposure a plus)

Requirements (Must-Haves)
  • Strong proficiency in modern C++ (C++17 or newer) — required

  • Solid experience working in UNIX/Linux environments

  • Hands-on experience with GDB for debugging complex systems

  • Familiarity with message buses / messaging systems (e.g., Kafka, ZeroMQ, custom pub/sub)

  • Strong systems fundamentals: memory management, concurrency, performance tradeoffs

  • Ability to write clean, modular, and well-tested code

Nice-to-Haves
  • Exposure to trading systems, market data, or execution infrastructure

  • Experience with Python for tooling, testing, or research integration

  • Familiarity with networking concepts (TCP/IP, latency considerations)

  • Experience with Docker or cloud environments (AWS)

  • Prior work on simulation, backtesting, or event-driven architectures

Why Join Blockhouse
  • Build real trading infrastructure used in live systematic strategies

  • Work directly on HFT-style systems, not toy or research-only projects

  • Direct mentorship from senior quant developers and ex-HFT engineers

  • High ownership and technical responsibility

  • Clear path to a return offer for strong performers

  • Fast-paced, engineering-driven culture with real production stakes

Compensation: $25 - 40 / hr cash + equity + PnL; structure depends on experience and availability. We offer benefits as well

International Students: CPT/OPT supported; flexible arrangements available.

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The Company
HQ: New York, New York
44 Employees
Year Founded: 2022

What We Do

Blockhouse is a financial data platform enhancing best execution with complex post-trade data visualizations and AI-powered analytics. Our technology enhances firms' best execution process - boosting execution efficiency and reducing transaction costs.

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