Feature Framework Engineer

Millennium•New York, NY

About The Position

The Systematic Platform Execution & Exchange Data (SPEED) Team is at the core of Millennium’s Equities, Quant Strategies, and Shared Services Technology organization, powering the firm’s lowest latency solutions for systematic and high frequency trading. SPEED delivers the live trading and market data platforms used by portfolio managers and risk systems, including Latency Critical Trading (LCT), DMA OMS (Client Direct), DMA market data feeds, packet capture (PCAPs), enterprise market data, and intraday data services across latency tiers from sub100 nanoseconds to millisecond sensitive workflows. By building and operating this execution and data infrastructure, SPEED enables portfolio managers and researchers to compete effectively in the most time-critical markets. As a Senior Feature Framework Developer on SPEED, you will design and build the most latency-critical components of our trading system. We are aiming for the best in class here. Additionally, you will work on making the platform more scalable. The system must grow along with data volumes while keeping a small footprint. You will collaborate with systems (Linux, network) engineers, senior software engineers as well as senior quantitative researchers, operate and optimize these systems in production, and have clear opportunities to grow into technical and team leadership as the effort scales. This role offers the chance to work end-to-end mission critical HFT systems in a highly technical environment, directly shaping the performance, reliability, and evolution of platforms that are central to Millennium’s trading edge. We are looking for a C++ engineer to design and build high‑performance, low‑latency applications that process large volumes of real‑time data. You will work on systems where nanoseconds and throughput matter, optimizing every layer from algorithms and data structures to networking and OS interaction.

Requirements

Strong proficiency in modern C++ (C++17/20 or later) 5+ years of experience
Analytics Focus:
KDB / Q Experience for large market data
Modern data analysis with pytorch, pandas and modern tooling including Apache arrow
Familiar with basics statistics as applied to financial research
Proven experience building performance‑critical, real‑time, or low‑latency systems (e.g., networking, trading systems, telemetry, gaming engines, or similar).
Strong knowledge of computer science fundamentals: data structures, algorithms, memory management, and optimization.
Experience using profiling, benchmarking, and performance analysis tools (e.g., perf, valgrind, flame graphs, CPU/memory profilers).
Proficiency with version control (Git) and standard build systems (CMake, Ninja, etc.).
Excellent problem‑solving skills and attention to detail; ability to work in a fast‑paced environment.
Strong interpersonal skills with a proven ability to navigate large organizations, create cross-team synergies, and influence outcomes.
High accountability and ownership; able to self-manage time, set priorities, and meet deadlines.

Nice To Haves

Experience with kernel bypass or user‑space networking technologies (e.g., DPDK, RDMA, VMA, Solarflare/OpenOnload) – helpful but not required.
Familiar with AI productivity enhancing coding tools
Experience in financial markets, market data distribution, order routing, or exchange connectivity.
Experience with monitoring/telemetry for high‑performance systems (latency histograms, throughput metrics, SLAs).
Familiarity with scripting languages (e.g., Python, Bash) for tooling and automation.
AI: Familiar with AI productivity enhancing coding tools.

Responsibilities

Design, implement, and maintain high‑performance C++ services handling high message rates and low‑latency workloads.
Optimize existing components for latency, throughput, and CPU/memory efficiency.
Develop and tune networking, messaging, and I/O layers to handle large data volumes reliably.
Profile and debug performance issues at application, OS, and network levels.
Collaborate with quantitative, trading, and infrastructure teams (or analogous business/tech teams) to translate requirements into robust technical solutions.
Write clean, production‑quality code with appropriate tests and documentation.
Participate in code reviews, design discussions, and continuous improvement of engineering practices.

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