Quantitative Developer, C++ I Low-Latency Systems

Millennium•New York, NY

1d•$150,000 - $200,000•Onsite

About The Position

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.

Requirements

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

Nice To Haves

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

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