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- Tasks: Design and operate systems for GPU-accelerated workloads and data-intensive applications.
- Company: Join a cutting-edge tech company in London with a hybrid work model.
- Benefits: Enjoy competitive salary, health benefits, and opportunities for professional growth.
- Why this job: Be at the forefront of AI and ML, making a real-world impact.
- Qualifications: Experience in platform engineering, data engineering, and strong Linux skills required.
- Other info: Collaborate with top researchers and engineers in a dynamic environment.
The predicted salary is between 54000 - 84000 £ per year.
We are building a next-generation computational platform that powers large-scale machine learning, data science, and scientific discovery. Our teams work at the intersection of cloud infrastructure, high-performance computing, and data engineering, enabling researchers and ML practitioners to move faster—from experimentation to real-world impact.
This role sits at the heart of the platform: designing, scaling, and operating systems that support GPU-accelerated workloads, batch pipelines, and data-intensive applications.
- Supporting ML training, inference, and experimentation at scale
- Hybrid cloud and on-prem compute
- Performance, reliability, and cost optimisation
- Large-scale data pipelines and data platforms
- Data reliability, orchestration, and observability
- Close collaboration with ML and research teams
- Designing and evolving Kubernetes-based compute platforms across hybrid and multi-cloud environments
- Building and operating GPU-enabled infrastructure for ML and scientific workloads
- Ensuring security, data protection, backup, and disaster recovery best practices
- Partnering closely with ML engineers, data scientists, and researchers to unblock compute and data challenges
- Platform/infrastructure engineering
- ML infrastructure or MLOps
- Data engineering at scale
- Solid experience with Linux and cloud environments
- Experience with Python (or similar) for automation or services
Bonus: Experience supporting ML training or data science teams.
Senior Engineer (Platform Engineering) in London employer: Hlx Life Sciences
Contact Detail:
Hlx Life Sciences Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Engineer (Platform Engineering) in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your projects, especially those related to platform engineering and ML infrastructure. This gives you a chance to demonstrate your expertise beyond just a CV.
✨Tip Number 3
Prepare for interviews by brushing up on technical questions and real-world scenarios. Practice explaining complex concepts simply, as you'll need to communicate effectively with both technical and non-technical teams.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are genuinely interested in joining our team.
We think you need these skills to ace Senior Engineer (Platform Engineering) in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Senior Engineer role. Highlight your experience in platform engineering, data pipelines, and any work with GPU-accelerated workloads to catch our eye!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about building next-gen computational platforms and how your background in ML infrastructure can contribute to our mission at StudySmarter.
Showcase Relevant Projects: If you've worked on projects involving Kubernetes, cloud environments, or data engineering, make sure to mention them. We love seeing real-world applications of your skills, so don’t hold back!
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 shows you’re keen on joining the StudySmarter team!
How to prepare for a job interview at Hlx Life Sciences
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, especially around Kubernetes, cloud environments, and GPU-accelerated workloads. Brush up on your Python skills too, as you might be asked to demonstrate your automation capabilities.
✨Showcase Your Collaboration Skills
This role involves working closely with ML engineers and data scientists, so be prepared to discuss past experiences where you’ve successfully collaborated on projects. Highlight how you’ve tackled compute and data challenges together, as teamwork is key in this position.
✨Prepare for Scenario-Based Questions
Expect questions that put you in real-world situations related to platform engineering. Think about how you would design a scalable system or optimise performance and reliability. Practising these scenarios can help you articulate your thought process clearly during the interview.
✨Understand the Company’s Vision
Research the company’s mission and recent projects. Being able to align your answers with their goals shows genuine interest and helps you stand out. Discuss how your skills can contribute to their next-generation computational platform and make an impact in the field.
