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- Tasks: Design and operate systems for GPU-accelerated workloads and data-intensive applications.
- Company: Innovative tech company focused on next-gen computational platforms.
- Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
- Why this job: Join a team making real-world impact in AI and machine learning.
- Qualifications: Experience in cloud environments, Linux, and Python for automation.
- Other info: Collaborative environment with strong focus on performance and reliability.
The predicted salary is between 48000 - 72000 £ 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
- 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 AWS Engineer/Platform Engineer | 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 AWS Engineer/Platform Engineer | in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. We all know that sometimes it’s not just what you know, but who you know that can get you in the door.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repo showcasing your projects, especially those related to AWS and ML infrastructure. This gives potential employers a taste of what you can do before they even meet you.
✨Tip Number 3
Prepare for the interview like it’s a big exam. Research the company, understand their tech stack, and be ready to discuss how your experience aligns with their needs. We want to see you shine!
✨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 proactive about their job search.
We think you need these skills to ace Senior AWS Engineer/Platform 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 AWS Engineer role. Highlight your experience with cloud infrastructure, data engineering, and any relevant projects you've worked on.
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.
Showcase Your Technical Skills: Don’t forget to mention your proficiency in Linux, Python, and any experience with Kubernetes or GPU-enabled infrastructure. We want to see how you can contribute to our platform right from the start!
Apply Through Our Website: For the best chance of getting noticed, apply directly through our website. It helps us keep track of your application and ensures it reaches the right team quickly!
How to prepare for a job interview at Hlx Life Sciences
✨Know Your Tech Inside Out
Make sure you brush up on your knowledge of AWS, Kubernetes, and GPU-accelerated workloads. Be ready to discuss specific projects where you've designed or operated systems in these areas. The more you can demonstrate your hands-on experience, the better!
✨Showcase Your Collaboration Skills
This role involves working closely with ML engineers and data scientists, so be prepared to share examples of how you've successfully collaborated in the past. Highlight any experiences where you’ve unblocked challenges for teams or improved workflows.
✨Prepare for Problem-Solving Questions
Expect to face technical problem-solving scenarios during the interview. Practice articulating your thought process clearly as you tackle these challenges. This will show your analytical skills and how you approach complex issues in platform engineering.
✨Understand the Company’s Vision
Familiarise yourself with the company’s mission around machine learning and scientific discovery. Being able to align your personal goals with their vision will not only impress the interviewers but also help you articulate why you’re a great fit for the team.
