10+ years in ultra-low latency networks within HFT or quantitative funds, with knowledge of exchange colocation and order routing protocols (FIX, OUCH, ITCH)
Advanced Python skills, particularly with libraries like pandas and numpy for data analysis
Hands-on experience with network testing labs and hardware traffic generators (Spirent/Ixia)
Expertise in Arista and Cisco hardware, with familiarity in FPGA applications for trading
Deep understanding of BGP/OSPF, Linux network tuning, and time synchronization protocols (PTP, White Rabbit)
Proficiency in network automation tools like Ansible and SQL, along with observability stacks like Prometheus and Grafana
Responsibilities
Establish and run a dedicated network testing lab for hardware evaluation
Design automated benchmark frameworks using traffic generators to validate network protocols
Build custom Python pipelines for analyzing high-volume packet captures and telemetry data
Architect and maintain low latency trading networks across global exchange colocation sites
Oversee time synchronization systems, ensuring precision in trading operations
Design and maintain large-scale L2/L3 architectures for resilient market data delivery
Stay updated on emerging low-latency networking technologies and recommend improvements
Benefits
Comprehensive health insurance coverage
Retirement savings plan with company matching
Generous paid time off and holiday schedule
Professional development opportunities and training
Flexible work arrangements and remote work options
Full Job Description
Hudson River Trading (HRT) is seeking an Ultra-Low Latency Network Architect to build, test, and optimize our global high-frequency trading infrastructure. In this role, you will lead hardware evaluation and lab benchmarking while leveraging Python and data analysis techniques to analyze high-volume PCAP captures, telemetry streams, and tick-to-trade latency distributions. You will bridge low-level network engineering with performance engineering teams to reduce jitter and push network performance into the single nanosecond domain.
Responsibilities
Hardware Evaluation & Lab Testing: Establish and run a dedicated network testing lab. Design automated benchmark frameworks using traffic generators (Spirent/Ixia) to simulate, measure and validate various protocols at a network level and to stress-test SmartNICs, switches, FPGAs, and transceivers
Network Data Analysis & Telemetry Pipeline: Build custom Python pipelines to process, analyze, and visualize high-volume packet captures (PCAPs), queue depth metrics, and telemetry data from FPGA/Corvil appliances to pinpoint anomalies. Write tools to automate lab testing procedures, parse binary network logs, and generate latency-distribution reports (e.g., 99.99th percentile jitter analysis)
HFT Architecture & Co-location: Architect and maintain low latency trading networks across global exchange colocation sites. Optimize trading network signals over wireless low-latency backhaul networks
Kernel Bypass & Acceleration: Familiarity with kernel-bypass stacks (AMD/Solarflare Onload/DPDK), hardware accelerator cards and layer-1/2 FPGA switches to minimize execution overhead. Collaborate with hardware engineering teams to benchmark performance for embedded network components such as network adapters and/or network co-processors
Time Synchronization: Oversee PTP (IEEE 1588v2) and White Rabbit time synchronisation systems
Routing and Switching: Design and maintain large-scale L2/L3 architectures specifically fine-tuning BGP, OSPF and PIM-SSM/IGMP multicast trees for sub-microsecond convergence and resilient market data delivery
Maintain Industry Awareness: Stay current with emerging low-latency networking technologies, including new SmartNICs, FPGA acceleration, and high-speed transceivers. Evaluate and recommend new hardware and software solutions to improve network performance
Qualifications
10+ years designing and operating ultra-low latency networks within HFT, market making, or quantitative fund environments. Knowledge of exchange colocation, market data feeds, and order routing protocols (FIX, OUCH, ITCH) is essential
Advanced Python skills using libraries like pandas, numpy, or pyarrow to parse large PCAP datasets, analyze time-series telemetry, and calculate microsecond/nanosecond statistics
Hands-on experience building network testing labs, using hardware traffic generators (Spirent/Ixia) and packet capture tools
Expertise with Arista (7130 series), Cisco (Nexus 3550/3548), LDA L1 switches, AMD Solarflare, and NVIDIA Mellanox hardware. Familiarity with FPGA driven low latency applications or custom accelerator cards in the context of high performance trading environments
Deep knowledge of BGP/OSPF, Linux network stack tuning, PTP (IEEE 1588), White Rabbit, PIM-SSM multicast, and large scale L2/L3 topologies. Awareness and experience with AI inference networks is a plus but not required
Proficiency with Ansible, SQL and Python network automation tools (e.g., Scapy, Netmiko, or AsyncIO) for config generation and orchestration. Experience with observability stacks such as Victoriametrics, Prometheus, Grafana, and Docker
The estimated base salary range for this position is 200,000 to 300,000 USD per year (or local equivalent). The base pay offered may vary depending on multiple individualized factors, including location, job-related knowledge, skills, and experience. This role will also be eligible for discretionary performance-based bonuses and a competitive benefits package.
About Hudson River Trading
Hudson River Trading (HRT) is a multi-asset class quantitative trading firm, and more specifically a high-frequency trading (HFT) firm, based in New York City and founded in 2002. The company is a global liquidity provider and market maker, operating in markets across the world, including equities, futures, options, currencies, and fixed income. HRT uses advanced technology and algorithms to analyze market data and execute trades at high speeds, with a focus on providing liquidity to the markets and minimizing risk. The company is known for its innovative approach to trading and its use of cutting-edge technology, including machine learning and artificial intelligence.
