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- Tasks: Design and operate cutting-edge platforms for AI and machine learning at scale.
- Company: Join a forward-thinking tech company focused on AI innovation.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on emerging AI technologies.
- Why this job: Make a real impact by solving complex platform challenges in AI.
- Qualifications: Experience in platform engineering and Kubernetes, with a passion for AI.
The predicted salary is between 70000 - 90000 £ per year.
Build and operate the platforms that make AI and machine learning work at scale.
We're looking for a Senior Platform Engineer to join our team and play a key role in designing and operating the platform that underpins AI and machine learning delivery. This is a hands-on senior platform role, focused on building robust, Kubernetes-based platforms that enable MLOps engineers, ML engineers, and data scientists to deploy, run, and manage models safely and effectively in production.
While you'll need a strong understanding of how machine learning and LLM workloads are trained, packaged, deployed, and served, this is not a "deploy models all day" role. You'll be responsible for building a production-grade AI / ML platform, not just running clusters.
- Design, build, and operate a Kubernetes-based platform that supports multiple ML and engineering teams.
- Model packaging, deployment, and promotion.
- Build shared platform services that enable consistent, repeatable model deployment, even where day-to-day deployment is owned by MLOps or ML engineers.
- Work closely with data scientists and MLOps engineers to ensure the platform is genuinely usable and fit for purpose.
- Contribute to architectural decisions while remaining hands-on with implementation.
This role is ideal for someone who sees themselves first and foremost as a platform engineer, with the depth to support AI and ML workloads properly.
- Strong background as a Senior Platform Engineer or Senior DevOps Engineer.
- Deep, hands-on experience building and operating Kubernetes-based platforms.
- Proven experience building internal platforms for other engineers, not just running workloads.
- Strong grasp of operational fundamentals: monitoring, logging, reliability, incidents, and maintainability.
- Comfortable collaborating closely with MLOps engineers and data scientists, even where responsibilities differ.
- ML platform & MLOps knowledge (important).
You don't need to be a full-time MLOps engineer - but you do need practical understanding of how ML and AI workloads behave in production.
- Supporting LLM-based workloads, including performance and scaling considerations.
- Awareness of emerging tooling around Responsible / Trustworthy AI or comparable solutions.
This ensures you're building a platform that actually works for AI use cases - not a generic compute layer. Working in organisations with a clear AI or data platform strategy. Supporting data scientists or ML engineers at scale.
If you enjoy solving hard platform problems and understand that AI places real, specific demands on infrastructure, this role gives you the space and responsibility to make a genuine impact.
Senior Digital Platforms Engineer in London employer: Lorien
Contact Detail:
Lorien Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Digital Platforms Engineer in London
✨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 Kubernetes and AI/ML platforms. This gives potential employers a taste of what you can do beyond just a CV.
✨Tip Number 3
Prepare for technical interviews by brushing up on your knowledge of MLOps and Kubernetes. Practice common interview questions and scenarios that relate to building and operating platforms, so you can demonstrate your expertise.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Tailor your application to highlight your platform engineering experience and how it aligns with our mission in AI and ML.
We think you need these skills to ace Senior Digital Platforms Engineer in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Senior Platform Engineer role. Highlight your hands-on experience with Kubernetes and any projects where you've built platforms for ML and AI workloads.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about platform engineering and how your background makes you a great fit for our team. Mention specific examples of how you've contributed to building robust platforms in the past.
Showcase Your Technical Skills: In your application, don't shy away from detailing your technical expertise. We want to see your understanding of operational fundamentals like monitoring and reliability, as well as your experience with MLOps and AI workloads.
Apply Through Our Website: We encourage you to apply directly through our website. This way, we can easily track your application and ensure it gets the attention it deserves. Plus, it shows us you're keen on joining the StudySmarter family!
How to prepare for a job interview at Lorien
✨Know Your Kubernetes Inside Out
Make sure you brush up on your Kubernetes skills before the interview. Be ready to discuss how you've built and operated Kubernetes-based platforms in the past, and think of specific examples where you've tackled challenges related to scaling and reliability.
✨Understand AI and ML Workloads
Familiarise yourself with how AI and machine learning workloads are packaged, deployed, and served. Be prepared to talk about your experience with MLOps and how you've collaborated with data scientists to ensure the platform meets their needs.
✨Showcase Your Problem-Solving Skills
This role is all about solving hard platform problems. Think of a few scenarios where you've had to troubleshoot or innovate under pressure. Share these stories during your interview to demonstrate your hands-on experience and critical thinking.
✨Stay Updated on Emerging Tools
Keep an eye on the latest trends and tools in Responsible AI and trustworthy solutions. Being able to discuss these topics will show that you're not just technically savvy but also forward-thinking, which is crucial for building a platform that works for AI use cases.