At a Glance
- Tasks: Design and optimise large-scale GPU compute clusters for cutting-edge algorithmic trading.
- Company: Top algorithmic trading firm with a scientific approach to finance.
- Benefits: Diverse team, innovative environment, and opportunities for impactful work.
- Other info: Equal opportunity employer valuing diverse perspectives and backgrounds.
- Why this job: Join a community of innovators at the forefront of automated trading technology.
- Qualifications: 5+ years in Linux systems engineering and expertise in GPU optimisation.
The predicted salary is between 80000 - 100000 £ per year.
One of the world’s top algorithmic trading firms, our client is looking for GPU Systems Engineers to help scale and evolve their exceptionally sophisticated HPC/AI research environment. Joining the Research and Development team, you will collaborate with experts responsible for the compute, storage, operating systems, and automation tools that enable trading and research to run 24/7 across the globe. They 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
Culture
This fund brings a scientific approach to trading financial products. They’ve built one of the world’s most sophisticated computing environments for research and development, and their researchers are at the forefront of innovation in the world of algorithmic trading. Colleagues come from all sorts of backgrounds: mathematics, computer science, statistics, physics, and engineering. A community of self‑starters who are motivated by the excitement of being at the cutting edge of automated trading, and their culture celebrates great ideas whether they come from veterans or new hires.
Seem like something you might be interested in? The goal is to find the best people and bring them together to do great work in a place where everyone is valued. They’re proud of their diverse staff; with offices all over the globe they benefit from varied and unique perspectives. This is an equal opportunity employer; so whoever you are they’d love to get to know you.
Contact: George Hutchinson‑Binks
GPU Systems Engineer- Tech-Driven Algorithmic Fund in London employer: Energy Jobline ZR
As a leading algorithmic trading firm in London, we pride ourselves on fostering a dynamic and inclusive work environment where innovation thrives. Our GPU Systems Engineers play a pivotal role in shaping cutting-edge HPC/AI research, with ample opportunities for professional growth and collaboration across diverse teams. With a commitment to employee development and a culture that values every voice, we offer a unique chance to be part of a high-impact organisation at the forefront of technology and finance.
StudySmarter Expert Advice🤫
We think this is how you could land GPU Systems Engineer- Tech-Driven Algorithmic Fund in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. We all know that sometimes it’s not just what you know, but who you know that can help you land that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your projects and contributions. This is a great way for us to demonstrate our expertise in GPU systems engineering and catch the eye of potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on technical questions related to HPC and GPU workloads. We should also be ready to discuss our past experiences and how they relate to the role. Practice makes perfect!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are genuinely interested in joining our tech-driven team.
We think you need these skills to ace GPU Systems Engineer- Tech-Driven Algorithmic Fund in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to highlight your experience in large-scale Linux systems engineering and GPU optimisation. We want to see how your skills align with the responsibilities listed in the job description, so don’t hold back!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re excited about the role and how your background makes you a perfect fit. We love seeing genuine enthusiasm for the work we do at StudySmarter.
Showcase Your Projects:If you've worked on relevant projects, make sure to include them! Whether it's automating system deployments or optimising GPU workloads, we want to see concrete examples of your expertise and impact.
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it gives you a chance to explore more about what we do at StudySmarter.
How to prepare for a job interview at Energy Jobline ZR
✨Know Your Tech Inside Out
Make sure you brush up on your knowledge of GPU systems, Linux engineering, and performance tuning. Be ready to discuss specific projects where you've optimised large-scale distributed GPU compute clusters or resolved performance bottlenecks.
✨Showcase Your Collaboration Skills
This role involves working closely with research and development teams. Prepare examples of how you've successfully collaborated with diverse technical teams in the past, especially in fast-paced environments. Highlight your communication skills and how they helped achieve project goals.
✨Demonstrate Problem-Solving Abilities
Be prepared to tackle hypothetical scenarios related to troubleshooting complex system issues. Think about how you would approach diagnosing problems at the hardware, OS, and network levels, and be ready to share your thought process during the interview.
✨Familiarise Yourself with Their Culture
Understand the company's scientific approach to trading and their emphasis on innovation. Be ready to discuss how your background and experiences align with their values, and express your excitement about contributing to a cutting-edge environment.
