Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Design and operate cutting-edge platforms for machine learning and data science.
- Company: Innovative tech firm in London with a hybrid work culture.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Why this job: Join a team at the forefront of technology and make a real-world impact.
- Qualifications: Experience in platform engineering, ML infrastructure, or data engineering.
- Other info: Dynamic role with excellent career advancement opportunities.
The predicted salary is between 48000 - 72000 £ per year.
Location: London (Hybrid)
Employment Type: Full-time
The Opportunity
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.
Who This Role Is For (Choose Your Strength)
- AI Platform / ML Infrastructure Engineers: Kubernetes-based compute platforms, GPU scheduling, batch & distributed workloads, supporting ML training, inference, and experimentation at scale.
- HPC / GPU Engineers: Job schedulers, MPI, multi-node workloads, hybrid cloud and on-prem compute, performance, reliability, and cost optimisation.
- Strong Data Engineers: Large-scale data pipelines and data platforms, data reliability, orchestration, and observability, close collaboration with ML and research teams.
What You’ll Work On
- Designing and evolving Kubernetes-based compute platforms across hybrid and multi-cloud environments.
- Building and operating GPU-enabled infrastructure for ML and scientific workloads.
- Developing and maintaining core platform services, APIs, and internal tooling.
- Improving CI/CD pipelines and Infrastructure-as-Code workflows.
- Implementing monitoring, alerting, and reliability engineering practices.
- 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.
What We’re Looking For
- Strong experience in one or more of: platform/infrastructure engineering, ML infrastructure or MLOps, HPC or GPU compute, data engineering at scale.
- Solid experience with Linux and cloud environments.
- Hands-on work with Kubernetes or distributed systems.
- Experience with Python (or similar) for automation or services.
- Familiarity with CI/CD, Git-based workflows, and automation.
- Strong problem-solving skills and a collaborative mindset.
Bonus
- Terraform or other IaC tools.
- Slurm, Kueue, Ray, Spark, or similar systems.
- GPU tooling (CUDA, Nvidia operators, schedulers).
- Experience supporting ML training or data science teams.
Platform Engineer in Slough employer: Hlx Life Sciences
Contact Detail:
Hlx Life Sciences Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Platform Engineer in Slough
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repo showcasing your projects, especially those related to Kubernetes or ML infrastructure. It’s a great way to demonstrate what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on common technical questions and scenarios related to platform engineering. Practice makes perfect, so get a mate to do mock interviews with you!
✨Tip Number 4
Don’t forget to apply through our website! We love seeing candidates who are genuinely interested in joining us at StudySmarter. Plus, it gives you a better chance to stand out!
We think you need these skills to ace Platform Engineer in Slough
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Platform Engineer role. Highlight your experience with Kubernetes, cloud environments, and any relevant projects that showcase your problem-solving abilities.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about building next-gen computational platforms. Share specific examples of how you've tackled challenges in ML infrastructure or data engineering, and how you can contribute to our team.
Showcase Your Technical Skills: Don’t shy away from listing your technical proficiencies! Whether it’s Python, CI/CD workflows, or GPU tooling, make sure we see your hands-on experience. This is your chance to shine and show us what you bring to the table.
Apply Through Our Website: We encourage you to apply directly through our website for the best chance of getting noticed. It’s super easy, and you’ll be able to keep track of your application status. Plus, we love seeing applications come in through our own platform!
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, like Kubernetes, Python, and cloud environments. Brush up on your knowledge of GPU scheduling and data pipelines, as these are crucial for the role.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific challenges you've faced in previous roles and how you tackled them. Use examples that highlight your collaborative mindset and ability to work with ML engineers and data scientists.
✨Familiarise Yourself with CI/CD Practices
Since the role involves improving CI/CD pipelines, be ready to talk about your experience with Git-based workflows and automation. Share any relevant projects where you implemented Infrastructure-as-Code or similar practices.
✨Ask Insightful Questions
Interviews are a two-way street! Prepare thoughtful questions about the team’s current projects, challenges they face, and how they measure success. This shows your genuine interest in the role and helps you assess if it’s the right fit for you.
