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# Quantitative Developer, C++ I Low-Latency Systems

- **Company:** MILLENNIUM
- **Location:** New York, NY, United States
- **Experience:** Experienced
- **Salary:** $150,000.0 - $200,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Algorithmic Trading, Amazon Web Services, Apache HTTP Server, Server Applications, Systems Engineering, Unit Testing, C++ (Programming Language), Cloud Computing, Databases, Continuous Integration, Data Structures, Cursor (Graphical User Interface Elements), Linux, Programming Tools, Memory Management, Interoperability, Python (Programming Language), Network Programming, NumPy, Performance Tuning, Systems Development Life Cycle, Software Construction, Systems Integration, Data Logging, Multithreading, Git, Pandas, Event Driven Architecture, Build Management, Containerization, Information Technology, Low Latency, Maintaining Code
- **Published:** June 10, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=0e3e537d8c538b85

## About the Role

Do you have experience in Unit testing?, Do you have a Bachelor's degree?, * Bachelor's or Master's degree in Computer Science, Mathematics, Physics, Engineering, or a related quantitative field

 * 3+ years of hands-on experience developing high-performance C++ server-side applications in Linux
 * Strong understanding of real-time and event-driven architectures with tight latency requirements
 * Proficiency in Python with working knowledge of Polars, Pandas, NumPy, and the PyData ecosystem
 * Deep familiarity with Apache Arrow and columnar data formats for cross-language interoperability
 * Strong understanding of network programming, Linux OS internals, and systems optimization
 * Experience consuming real-time market data feeds and integrating with shared execution platforms
 * Solid understanding of data structures, algorithms, and concurrent/multithreaded programming
 * Proficiency with Git, CI/CD, unit testing, and software engineering best practices.
 * Experience with AI-assisted coding tools (Cursor, Claude Code, Copilot) and willingness to integrate them into daily workflow

Preferred Skills / Experience

 * Experience building trading systems in a systematic equities or quant trading environment
 * Familiarity with low-latency optimization techniques: cache-friendly data structures, SIMD, memory-mapped I/O
 * Experience with Rust for performance-critical systems development
 * Experience with kdb+/q for time-series data
 * Knowledge of equity market microstructure, order types, and execution algorithms
 * Experience with DuckDB, Arrow Flight, or similar analytical database technologies
 * Familiarity with cloud infrastructure (AWS) and containerized deployments

## Description

We are seeking a highly skilled C++ developer to architect, build, and maintain the core signal computation and alpha Infrastructure for a newly formed systematic equities pod. You will own the hot path - real-time feature computation, signal generation, and Integration with the firm's shared execution and market data platforms - and play a foundational role in shaping the technology stack from day one.

This is a hands-on role at the intersection of systems engineering and quantitative research. You will work directly with the Portfolio Manager and quantitative researchers to translate alpha signals into production-ready, high-performance trading systems.

Principal Responsibilities

 * Design and build the core C++ signal engine: real-time feature computation, alpha signal generation, position tracking, and risk monitoring
 * Architect the data bridge between the C++ hot path and the Python/Polars research layer
 * Implement and optimize real-time alpha signal publication from the research pipeline into the firm's shared execution infrastructure
 * Integrate with the firm's central market data feeds and execution platforms
 * Develop real-time risk checks, position monitoring, logging, and alerting infrastructure
 * Optimize system performance: latency profiling, lock-free data structures, memory management, and network tuning
 * Collaborate closely with quantitative researchers to understand strategy requirements and translate prototypes (Python) into production-grade C++ code
 * Leverage Al-assisted development tools (Cursor, Claude Code) to accelerate

development velocity while maintaining code quality

 * Build and maintain backtesting and exchange simulation infrastructure for strategy validation


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