At a Glance
- Tasks: Design and maintain MLOps infrastructure for machine learning lifecycle management.
- Company: Join a leading tech firm in London focused on AI innovation.
- Benefits: Competitive salary, hands-on experience, and opportunities for growth.
- Other info: Dynamic team environment with excellent career advancement potential.
- Why this job: Be at the forefront of AI technology and make a real impact.
- Qualifications: Strong MLOps experience and proficiency in cloud platforms required.
The predicted salary is between 60000 - 80000 € per year.
Location: London, UK
Work Model: On-site
Role Type: Full-Time
We are looking for an MLOps Engineer with strong experience in AI infrastructure and machine learning deployment to join our client’s on-site team in London. This role focuses on building scalable MLOps platforms and deployment pipelines that enable reliable, efficient, and production-ready machine learning systems.
- Design and maintain MLOps infrastructure supporting machine learning lifecycle management
- Build CI/CD pipelines for training, testing, deployment, and monitoring of ML models
- Deploy and manage machine learning workloads in cloud environments
- Automate model versioning, retraining, and performance monitoring workflows
- Collaborate with data scientists and engineering teams to productionise AI systems
- Improve scalability, observability, and reliability of ML platforms
- Implement Infrastructure as Code and automation best practices
What We’re Looking For
- Required Skills & Experience
- Strong experience with MLOps workflows and AI infrastructure
- Experience with cloud platforms such as Amazon Web Services, Google Cloud, or Microsoft Azure
- Experience with containerisation using Docker and orchestration via Kubernetes
- Strong Python and automation skills
- Experience with CI/CD pipelines and Infrastructure as Code
- Familiarity with monitoring and observability tools
- Nice to Have
- Experience with feature stores and experiment tracking
- Familiarity with GenAI and LLM deployment workflows
- Experience with distributed ML training systems
- Knowledge of model governance and AI compliance practices
MLOps Engineer – AI Infrastructure & Deployment employer: Talenzon group
Join a dynamic team in London as an MLOps Engineer, where you will be at the forefront of AI infrastructure and deployment. Our company fosters a collaborative work culture that prioritises innovation and professional growth, offering ample opportunities for skill development and career advancement. With a focus on cutting-edge technology and a commitment to employee well-being, we provide a rewarding environment for those looking to make a meaningful impact in the field of machine learning.
StudySmarter Expert Advice🤫
We think this is how you could land MLOps Engineer – AI Infrastructure & Deployment
✨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 refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your MLOps projects, CI/CD pipelines, and any cool stuff you've built. This gives you a chance to demonstrate your expertise beyond just words on a CV.
✨Tip Number 3
Prepare for interviews by brushing up on common MLOps scenarios and challenges. Practice explaining your thought process and how you tackle problems, as this will help you stand out during technical interviews.
✨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 MLOps Engineer – AI Infrastructure & Deployment
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with MLOps workflows and AI infrastructure. We want to see how your skills align with the role, so don’t be shy about showcasing your cloud platform expertise and containerisation know-how!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re passionate about MLOps and how your background makes you a perfect fit for our team. Let us know what excites you about working in AI infrastructure and deployment.
Showcase Relevant Projects:If you've worked on any projects related to CI/CD pipelines or machine learning deployment, make sure to mention them! We love seeing real-world applications of your skills, so include links or descriptions that highlight your contributions.
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 our company culture and values!
How to prepare for a job interview at Talenzon group
✨Know Your MLOps Inside Out
Make sure you brush up on your MLOps workflows and AI infrastructure knowledge. Be ready to discuss specific projects where you've built scalable platforms or deployment pipelines. This will show that you not only understand the theory but have practical experience too.
✨Cloud Platforms Are Key
Familiarise yourself with the cloud platforms mentioned in the job description, like AWS, Google Cloud, or Azure. Have examples ready of how you've deployed machine learning workloads in these environments, as this will demonstrate your hands-on expertise.
✨Show Off Your CI/CD Skills
Be prepared to talk about your experience with CI/CD pipelines and Infrastructure as Code. Bring examples of how you've automated model versioning or retraining processes, as this is crucial for the role and will highlight your ability to streamline workflows.
✨Collaboration is Key
Since you'll be working closely with data scientists and engineering teams, think of examples where you've successfully collaborated on projects. Highlight how you’ve contributed to productionising AI systems and improving the reliability of ML platforms.
