Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Lead the design and development of scalable ML systems using Python and cloud technologies.
- Company: Omnis Partners, a forward-thinking company shaping the future of ML engineering.
- Benefits: Flexible/hybrid working, competitive salary, and opportunities for professional growth.
- Other info: Dynamic team environment with a focus on best practices in ML delivery.
- Why this job: Join us to make a real impact in the world of machine learning at scale.
- Qualifications: Expertise in Python, cloud platforms, and experience with TensorFlow or PyTorch.
The predicted salary is between 60000 - 80000 £ per year.
Omnis Partners is seeking a software engineer with a strong background in building production ML systems. In this role, you'll be responsible for leading architecture and design, developing scalable software, and driving best practices in ML delivery.
The ideal candidate will have:
- Expert Python skills
- Cloud experience (AWS/Azure/GCP)
- Hands-on experience with TensorFlow or PyTorch
The role offers flexible/hybrid working and a chance to shape ML engineering at scale.
Production ML Systems Engineer - Python, Kubernetes, Cloud in London employer: Omnis Partners
Contact Detail:
Omnis Partners Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Production ML Systems Engineer - Python, Kubernetes, Cloud 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 showcasing your projects, especially those involving Python, Kubernetes, and ML systems. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and understanding the latest trends in ML and cloud technologies. Practice common interview questions and be ready to discuss your past experiences in detail.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Plus, it’s a great way to ensure your application gets seen by the right people.
We think you need these skills to ace Production ML Systems Engineer - Python, Kubernetes, Cloud in London
Some tips for your application 🫡
Show Off Your Python Skills: Make sure to highlight your expert Python skills in your application. We want to see how you've used Python in real-world projects, especially in building production ML systems.
Cloud Experience is Key: Don’t forget to mention your experience with cloud platforms like AWS, Azure, or GCP. We’re looking for someone who can navigate these environments smoothly, so share any relevant projects you've worked on.
Talk About Your ML Frameworks: If you’ve got hands-on experience with TensorFlow or PyTorch, let us know! We love seeing how you’ve applied these frameworks in your work, so include specific examples in your application.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you don’t miss out on any important updates!
How to prepare for a job interview at Omnis Partners
✨Know Your Tech Stack Inside Out
Make sure you’re well-versed in Python, Kubernetes, and the cloud platforms mentioned in the job description. Brush up on your knowledge of TensorFlow or PyTorch, as you might be asked to discuss specific projects where you've used these technologies.
✨Showcase Your Problem-Solving Skills
Prepare to discuss how you've tackled challenges in building production ML systems. Think of examples where you led architecture and design decisions, and be ready to explain your thought process and the impact of your solutions.
✨Understand Best Practices in ML Delivery
Familiarise yourself with best practices in machine learning delivery. Be prepared to talk about how you ensure scalability and reliability in your projects, and how you keep up with industry trends and advancements.
✨Ask Insightful Questions
At the end of the interview, don’t shy away from asking questions. Inquire about the team’s current projects, their approach to ML engineering, and how they envision the role evolving. This shows your genuine interest and helps you assess if it’s the right fit for you.