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: Competitive salary, diverse team, and opportunities for innovation.
- Other info: Fast-paced environment with excellent career growth and a focus on collaboration.
- Why this job: Join a dynamic team at the forefront of AI and HPC technology.
- Qualifications: 5+ years in Linux systems engineering and GPU optimisation experience required.
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 george.hutchinson-binks@oxfordknight.co.uk (+44) 07885 545220 linkedin.com/in/george-hutchinson-binks-a62a69252
GPU Systems Engineer- Tech-Driven Algorithmic Fund in London employer: Energy Jobline ZR
As a leading algorithmic trading firm in London, our client offers an exceptional work environment that fosters innovation and collaboration among experts in HPC and AI. Employees benefit from a culture that values diverse perspectives, encourages professional growth, and provides opportunities to work on cutting-edge technology in a fast-paced setting. With a commitment to equal opportunity and a focus on impactful projects, this is a place where your contributions are recognised and valued.
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 land you that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your projects and contributions. We want to see what you can do with GPU systems and how you tackle challenges in HPC/AI environments.
✨Tip Number 3
Prepare for those interviews! Brush up on your technical knowledge and be ready to discuss your experience with Linux systems and GPU optimisation. We’re here to help you practice and refine your answers.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. We’re excited to help you take the next step in your career journey!
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 the GPU Systems Engineer role. Highlight your experience with large-scale Linux systems, GPU optimization, and any relevant projects you've worked on. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about algorithmic trading and how your background in HPC/AI can contribute to our team. Keep it concise but impactful – we love a good story!
Show Off Your Technical Skills:Don’t hold back on showcasing your technical expertise! Mention your proficiency in Python scripting, experience with NVIDIA technologies, and any automation frameworks you’ve used. We’re keen to see how you can tackle complex system issues.
Apply Through Our Website:We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any important updates. Plus, it’s super easy!
How to prepare for a job interview at Energy Jobline ZR
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, especially around GPU optimisation and performance. Brush up on your Linux systems engineering skills and be ready to discuss specific experiences where you’ve tackled performance bottlenecks or automated system deployments.
✨Showcase Your Problem-Solving Skills
Prepare to share examples of how you've diagnosed and resolved complex system issues in past roles. Think about specific challenges you faced with distributed GPU workloads and how you approached troubleshooting them. This will demonstrate your hands-on experience and analytical thinking.
✨Collaborate and Communicate
Since this role involves working closely with research and development teams, be ready to discuss how you’ve successfully collaborated across diverse technical teams in the past. Highlight your communication skills and any tools you’ve used for configuration management, as these are key to thriving in their environment.
✨Be Ready for a Fast-Paced Environment
This firm thrives on high-impact work, so prepare to discuss how you handle pressure and fast-paced situations. Share examples of projects where you had to adapt quickly or manage multiple tasks simultaneously, showcasing your ability to thrive in dynamic settings.
