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For Companies At a Glance
- Tasks: Design and scale AI infrastructure for cutting-edge GPU systems.
- Company: Join a hyper-growth company at the forefront of AI technology.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Why this job: Make a real impact in AI by solving complex problems with a talented team.
- Qualifications: 5+ years in distributed systems, Kubernetes expertise, and a collaborative mindset.
- Other info: Work in a dynamic environment with significant ownership and career advancement.
The predicted salary is between 36000 - 60000 £ per year.
We’re working with a hyper growth company. They are building the GPU infrastructure to the best AI labs and the biggest enterprise companies. They are building the solution that allows researchers to focus on their models, while utilising the phenomenal scale and reliability of the world’s best AI cloud platform. The engineering team is small, ambitious, and deeply technical, building the orchestration systems that keep thousands of GPUs running at peak performance across global data centres. This role sits at the heart of it, designing and scaling the systems that make AI at exascale possible.
What You’ll Focus On
- You’ll help shape the orchestration layer for one of the most advanced AI compute environments in the world. Your work will involve:
- Designing core platform services for cluster provisioning, workload orchestration, and resource management APIs.
- Building integrations with schedulers (Kubernetes, Slurm) and container runtimes for reliable, high-performance GPU workloads.
- Developing automation for deployment, imaging, and multi-tenant resource allocation.
- Optimising scheduler performance and resource utilisation across diverse workloads.
- Building lifecycle management and automated remediation systems for large-scale clusters.
- Creating Infrastructure-as-Code modules to support rapid, repeatable deployments across varied environments.
About You
You’re a pragmatic systems builder who thrives in complexity, enjoys autonomy, and understands what it means to own production at scale. You’ll likely bring:
- 5+ years’ experience building distributed systems in Go within cloud-native environments.
- Deep hands-on experience with Kubernetes and container orchestration.
- A strong grasp of Infrastructure-as-Code (Terraform) and configuration management tools (Ansible, Puppet, or similar).
- Experience deploying and operating large-scale GPU clusters or HPC systems.
- Working knowledge of ML infrastructure and familiarity with GPU drivers, CUDA, and container runtimes.
- A low-ego, collaborative approach and a clear, proactive communication style.
In short: This is a role for engineers who like big systems, hard problems, and meaningful ownership. You’ll be joining a team operating at the intersection of software, hardware, and AI.
Staff Software Engineer employer: Motive Group
Contact Detail:
Motive Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Staff Software Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your projects, especially those related to distributed systems or AI infrastructure. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for technical interviews by brushing up on your knowledge of Kubernetes, Terraform, and GPU clusters. Practice coding challenges and system design questions to demonstrate your expertise during interviews.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented engineers like you. Plus, it’s a great way to ensure your application gets seen by the right people.
We think you need these skills to ace Staff Software Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that match the job description. Highlight your experience with distributed systems, Kubernetes, and GPU clusters to show us you’re the right fit!
Craft a Compelling Cover Letter: Use your cover letter to tell us why you’re passionate about AI infrastructure and how your background aligns with our needs. Be genuine and let your personality shine through!
Showcase Your Projects: If you've worked on relevant projects, don’t hesitate to include them! Whether it’s a personal project or something from your previous job, we want to see how you’ve tackled complex problems.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates!
How to prepare for a job interview at Motive Group
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, especially Go, Kubernetes, and Infrastructure-as-Code tools like Terraform. Brush up on your knowledge of GPU clusters and how they operate, as this will show your genuine interest and expertise.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific challenges you've faced in building distributed systems. Think of examples where you optimised performance or resolved complex issues. This will demonstrate your ability to tackle hard problems, which is key for this role.
✨Communicate Clearly and Collaboratively
Since the role requires a low-ego, collaborative approach, practice articulating your thoughts clearly. Be ready to explain your past projects and decisions in a way that highlights teamwork and proactive communication.
✨Ask Insightful Questions
Prepare thoughtful questions about the company’s AI infrastructure and the engineering team’s goals. This shows your enthusiasm for the role and helps you gauge if the company culture aligns with your values.
