At a Glance
- Tasks: Enhance AI infrastructure by optimising networking for large-scale training workloads.
- Company: Join Verda, a pioneering AI cloud company shaping the future of technology.
- Benefits: Enjoy a competitive salary, health perks, and a hybrid work model in vibrant cities.
- Other info: Collaborative environment with opportunities for personal and professional growth.
- Why this job: Be part of an innovative team making a real impact in AI infrastructure.
- Qualifications: Experience with distributed systems and communication libraries is essential.
The predicted salary is between 60000 - 80000 £ per year.
About Verda
Verda is reimagining cloud infrastructure for AI workloads. We are a full-stack AI cloud company, meaning we install, operate, and optimize our compute for training and inference of AI models. Join Verda while it’s still being built - not once it’s finished!
Your responsibilities
- Focus on improving the networking and communication layer behind large-scale LLM training workloads.
- Optimize collective communication performance across distributed GPU clusters, helping improve throughput, utilization, and reliability for communication‑bound workloads.
- Debug and analyze bottlenecks across the networking stack, building tooling and infrastructure for benchmarking, profiling, and regression testing of distributed training performance.
- Work closely with training, infrastructure, hardware, and networking teams to improve how workloads scale across clusters, contributing to both system reliability and overall training efficiency.
This role is highly collaborative and research‑adjacent, requiring curiosity, initiative, and willingness to go deep into low‑level communication systems and distributed training infrastructure.
Your key competencies
- Experience with distributed systems, networking, or large‑scale ML training infrastructure.
- Experience with communication libraries such as NCCL, MPI, NVSHMEM, or similar technologies.
- Experience with profiling and debugging tools such as Nsight Systems, NCCL logs, PyTorch Profiler, or perf.
- Strong systems thinking and ability to analyze performance bottlenecks across distributed environments.
- Self‑starter mindset with ability to independently define and drive technical projects.
- Strong curiosity about low‑level systems, networking, and large‑scale AI infrastructure.
Representative projects
- Build tools to identify NCCL bottlenecks, slow ranks, and communication tail latency.
- Build dashboards and regression infrastructure for training network health and performance.
- Implement fault‑tolerance mechanisms to reduce cluster idle time and improve training efficiency.
Practicalities
- Location: Helsinki, Finland or London, UK.
- Hybrid mode: Working from either our Helsinki or London office for three days a week.
- Employment type: Full‑time and permanent.
What’s next
We’re building fast and this role needs the right person behind it. There’s no artificial deadline, but when we find who we’re looking for, we move. If this sounds like your next move, apply now.
Member of Technical Staff, AI Infrastructure Team employer: Verda
Verda is an exceptional employer, offering a dynamic work environment where innovation meets collaboration in the heart of Helsinki or London. With a strong focus on employee growth, Verda provides opportunities to engage in cutting-edge AI infrastructure projects while fostering a culture of curiosity and initiative. Enjoy the benefits of a hybrid work model, competitive compensation, and the chance to be part of a pioneering team that is shaping the future of cloud infrastructure for AI workloads.
StudySmarter Expert Advice🤫
We think this is how you could land Member of Technical Staff, AI Infrastructure Team
✨Tip Number 1
Network, network, network! Reach out to folks in the AI and cloud infrastructure space. Attend meetups, webinars, or even just chat with people on LinkedIn. You never know who might have a lead on a role at Verda!
✨Tip Number 2
Show off your skills! If you’ve worked on projects related to distributed systems or AI infrastructure, create a portfolio or GitHub repo showcasing your work. This can really set you apart when you apply through our website.
✨Tip Number 3
Prepare for technical interviews by brushing up on your knowledge of communication libraries like NCCL or MPI. Practice explaining complex concepts simply; it shows you understand your stuff and can communicate effectively with the team.
✨Tip Number 4
Be curious! Research Verda’s projects and think about how you can contribute. When you apply, mention specific ideas or improvements you could bring to the table. It shows initiative and that you’re genuinely interested in being part of the team.
We think you need these skills to ace Member of Technical Staff, AI Infrastructure Team
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the role. Highlight your experience with distributed systems and networking, as well as any relevant projects you've worked on. We want to see how you can contribute to our AI infrastructure!
Craft a Compelling Cover Letter:Your cover letter is your chance to show us your personality and passion for the role. Explain why you're excited about working at Verda and how your background aligns with our mission. Don’t forget to mention your curiosity about low-level systems!
Showcase Relevant Projects:If you've worked on projects related to large-scale ML training or communication libraries, make sure to include them in your application. We love seeing practical examples of your work, especially if they demonstrate your problem-solving skills and initiative.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us that you’re serious about joining our team at Verda!
How to prepare for a job interview at Verda
✨Know Your Tech Inside Out
Make sure you brush up on your knowledge of distributed systems and networking. Familiarise yourself with communication libraries like NCCL and MPI, as well as profiling tools such as Nsight Systems. Being able to discuss these technologies confidently will show that you're serious about the role.
✨Show Your Curiosity
Verda values curiosity, so come prepared with questions about their AI infrastructure and how they tackle challenges in large-scale ML training. This not only demonstrates your interest but also gives you insight into their processes and culture.
✨Prepare for Technical Challenges
Expect to face some technical questions or scenarios during the interview. Practice explaining how you would approach debugging performance bottlenecks or building tools for benchmarking. Use real examples from your past experiences to illustrate your problem-solving skills.
✨Highlight Collaboration Skills
Since this role is highly collaborative, be ready to discuss your experience working with cross-functional teams. Share specific instances where you’ve successfully collaborated with others to improve system reliability or efficiency, showcasing your ability to work well in a team environment.
