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Niche HFT skillset but mid-level (3+ years) profile increases applicant density modestly.
Highly specialized trading and low-latency systems skills limit cross-industry transferability.
Multiple mandatory technical filters (expert Python, low-latency networking, exchange protocols) imply high selectivity.
Design, build, and optimize Python-based trading infrastructure including market data processing, order execution logic, and strategy runners with focus on low-latency and high throughput.
Develop and maintain tooling for research-to-production workflows, simulation, backtesting, monitoring, and risk control in a production trading system.
Profile and resolve performance bottlenecks and participate in incident response and on-call rotations for live trading platforms.
3+ years professional software engineering experience with significant exposure to performance-sensitive or production trading systems.
Expert-level Python skills including asyncio, concurrency/parallelism, NumPy/pandas, and performance optimization tools like Cython or Numba.
Solid understanding of networking fundamentals (TCP/UDP, multicast) and experience with exchange connectivity or market data protocols (FIX, WebSocket, REST, or proprietary).
Degree in Computer Science, Electrical Engineering, Mathematics, Physics, or related field (or equivalent experience).
Strong background in building and optimizing low-latency, high-performance trading systems using Python in production environments.
Experience collaborating with quantitative researchers and traders to implement and optimize strategy logic for live deployment.
Prior exposure to high-frequency trading, market-making, or proprietary trading environments considered a plus but not mandatory.