GPU Systems Engineer
Hudson River TradingLondon, United Kingdom; New York, NY, United States; Seattle, Washington, United States$150k – $300kPosted 24 February 2026
Job Description
Hudson River Trading (HRT) is looking for GPU Systems Engineers to help scale and evolve our exceptionally sophisticated HPC/AI research environment.
Joining our Research and Development team, you will collaborate with experts responsible for the compute, storage, operating systems, and automation tools that enable our trading and research to run 24/7 across the globe. We design, grow, and operate infrastructure at a large scale, including triple-digit petabyte-scale storage and massive CPU and GPU clusters in globally distributed data centers. As such, this is a high-impact role with broad scope, from HPC/AI cluster design and performance tuning, to troubleshooting and automation for thousands of nodes.
Responsibilities
Design, build, and optimize large-scale distributed GPU compute clusters
Identify and resolve GPU workloads’ performance bottlenecks across compute, storage, and networking layers
Collaborate with research and development teams to profile, benchmark, and fine-tune GPU-based workloads
Automate system deployment, monitoring, and troubleshooting across thousands of nodes
Collaborate with research, and engineering teams to support evolving workloads
Own critical infrastructure projects — from concept to implementation and support
Test and deploy new hardware and software, and partner with vendors to resolve complex issues
Qualifications
5+ years of experience in large-scale Linux systems engineering in HPC, AI or distributed infrastructure roles.
Extensive experience in Linux system installation, performance tuning, and troubleshooting
Expertise in troubleshooting distributed GPU workloads
Deep knowledge around GPU optimization and performance
Proficiency in Python scripting and automation frameworks
CUDA or C/C++ experience is a plus
Experience with NVIDIA technologies beyond CUDA, such as NCCL, GPUDirect RDMA, and NVLink
Familiarity with configuration management tools (e.g. Salt, Ansible, Puppet, Chef)
Comfortable diagnosing complex system issues at the hardware, OS, and network levels
Strong communication and organizational skills; able to collaborate across diverse technical teams
Thrive in fast-paced environments and excited by high-impact work
The estimated base salary range for this position is 150,000 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 which includes medical, dental, vision, basic life insurance, and enrollment in our company’s retirement savings plans. Employees will receive sick and parental leave, as well as other paid time off (including 20 vacation days and 10 paid holidays in the US). Please note that benefits and time off policies will vary across non-US locations.
Culture
Hudson River Trading (HRT) brings a scientific approach to trading financial products. We have built one of the world's most sophisticated computing environments for research and development. Our researchers are at the forefront of innovation in the world of algorithmic trading.
At HRT we welcome a variety of expertise: mathematics and computer science, physics and engineering, media and tech. We’re a community of self-starters who are motivated by the excitement of being at the cutting edge of automation in every part of our organization—from trading, to business operations, to recruiting and beyond. We value openness and transparency, and celebrate great ideas from HRT veterans and new hires alike. At HRT we’re friends and colleagues – whether we are sharing a meal, playing the latest board game, or writing elegant code. We embrace a culture of togetherness that extends far beyond the walls of our office.
Feel like you belong at HRT? Our goal is to find the best people and bring them together to do great work in a place where everyone is val ... (truncated, view full listing at source)
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