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- Tasks: Design and build MLOps platforms for AI and data science teams.
- Company: Join a forward-thinking engineering organisation focused on innovation.
- Benefits: Enjoy remote work, competitive salary, and opportunities for professional growth.
- Other info: Be part of a dynamic team with a focus on real-world impact.
- Why this job: Lead technical projects that shape the future of AI and machine learning.
- Qualifications: Strong background in platform engineering and hands-on Kubernetes experience.
The predicted salary is between 80000 - 100000 £ per year.
Building the platforms that make AI and machine learning work in production.
We're looking for a Lead Platform Engineer to join a growing engineering organisation and play a pivotal role in designing, building, and operating an MLOps platform that enables AI and data science teams to deliver reliably in production.
This is a senior, hands-on technical leadership role, not a people-management position. You'll lead through technical depth, judgement, and delivery, building the tooling, workflows, and operational foundations that allow data scientists and ML engineers to experiment, deploy, and run ML and LLM-based workloads safely and at scale.
You'll act as a technical leader across platform engineering, DevOps, and MLOps, remaining deeply involved in implementation.
- Provide technical leadership across platform, DevOps, and MLOps activities.
- Work closely with data scientists and ML engineers to ensure the platform is usable, well-documented, and aligned to real workflows.
- Apply pragmatic engineering judgement in environments where AI workloads place real operational demands on infrastructure.
This role suits someone who is fundamentally a strong platform engineer, with the depth to apply those skills confidently to MLOps.
- Strong background as a Senior or Lead Platform Engineer / DevOps Engineer.
- Deep, hands-on experience building and operating Kubernetes-based platforms.
- Strong understanding of operational fundamentals: monitoring, logging, incident response, reliability, and maintenance.
- Comfortable working directly with engineers and data scientists to support real production workloads.
- You'll work deeply 'in the weeds' of MLOps platforms, enabling ML and LLM workloads (not model research).
- Building or operating MLOps platforms using tools like Kubeflow or similar frameworks.
- Exposure to emerging tooling such as InstructLab, Trustworthy / Responsible AI tooling, or comparable solutions.
- Building internal platforms specifically for data science and ML teams.
- Operating AI-enabled or data-driven systems in production.
Remote Lead Platform Engineer in London employer: Lorien
Contact Detail:
Lorien Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Remote Lead Platform Engineer in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the tech world, especially those in MLOps or platform engineering. A friendly chat can lead to insider info about job openings that aren't even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Kubernetes or MLOps platforms. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for technical interviews by brushing up on your hands-on skills. Be ready to discuss your experience with operational fundamentals like monitoring and incident response, as these are crucial for the role.
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who are genuinely interested in joining our team. Plus, it makes the application process smoother for everyone involved.
We think you need these skills to ace Remote Lead Platform Engineer in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with MLOps and platform engineering. We want to see how your skills align with the role, so don’t be shy about showcasing your hands-on experience with Kubernetes and any relevant tools you've used.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about building platforms for AI and machine learning. We love seeing candidates who can connect their personal experiences to our mission at StudySmarter.
Showcase Your Technical Leadership: Since this is a senior role, we’re keen to see examples of your technical leadership. Share specific instances where you’ve led projects or made significant contributions to platform engineering, especially in MLOps environments.
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’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 Lorien
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, especially Kubernetes and MLOps tools like Kubeflow. Brush up on your operational fundamentals too, as you'll need to demonstrate your hands-on experience during the interview.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific challenges you've faced in previous roles, particularly around building and operating platforms for AI workloads. Use the STAR method (Situation, Task, Action, Result) to structure your answers and highlight your pragmatic engineering judgement.
✨Collaborate Like a Pro
Since this role involves working closely with data scientists and ML engineers, be ready to talk about how you’ve successfully collaborated with cross-functional teams in the past. Share examples of how you’ve ensured usability and alignment with real workflows.
✨Stay Current with Emerging Tools
Familiarise yourself with the latest trends and tools in the MLOps space, such as InstructLab or Responsible AI tooling. Being able to discuss these innovations will show that you’re not just technically skilled but also forward-thinking and adaptable.