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For Companies At a Glance
- Tasks: Own the reliability and scalability of machine-learning systems in research and production.
- Company: Join a forward-thinking tech company at the forefront of AI innovation.
- Benefits: Enjoy competitive pay, flexible working options, and opportunities for professional growth.
- Why this job: Make a real impact by ensuring ML systems run smoothly and efficiently.
- Qualifications: Experience in ML infrastructure and strong engineering skills required.
- Other info: Be part of a dynamic team with exciting projects and career advancement potential.
The predicted salary is between 60000 - 80000 £ per year.
Role Overview
We are hiring an ML Ops Engineer to own the reliability, scalability, and operational integrity of our machine-learning systems in research & production. This role sits at the intersection of data engineering and ML infrastructure: you'll design and operate data pipelines that feed models, and you'll build the tooling that trains, deploys, monitors, and retrains them.
You'll work closely with research engineers and product teams, taking models from experimentation to production-grade systems with clear SLAs, reproducibility guarantees, and observable behaviour. This is not a research role; it is a hands-on engineering role focused on making ML systems work reliably at scale.
What You'll Work On
- ML lifecycle infrastructure
- Productionizing models: packaging, deployment, versioning, and rollback
- Designing CI/CD pipelines for ML (training --> validation --> deployment)
- Implementing model monitoring (data drift, prediction drift, performance decay)
- Managing experiment tracking and reporting
Machine Learning Ops Engineer in London employer: CMC Markets UK Plc
Contact Detail:
CMC Markets UK Plc Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Ops Engineer in London
✨Tip Number 1
Network like a pro! Reach out to folks in the ML Ops community on LinkedIn or attend meetups. We can’t stress enough how valuable personal connections can be in landing that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects related to ML infrastructure and data pipelines. We love seeing practical examples of what you can do, so make sure to highlight your hands-on experience.
✨Tip Number 3
Prepare for technical interviews by brushing up on your CI/CD knowledge and model monitoring techniques. We recommend doing mock interviews with friends or using online platforms to get comfortable with the format.
✨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’re always on the lookout for passionate candidates who want to make an impact in ML Ops.
We think you need these skills to ace Machine Learning Ops Engineer in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in ML Ops and data engineering. We want to see how your skills align with the role, so don’t be shy about showcasing your projects and achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about ML Ops and how you can contribute to our team. Keep it engaging and personal – we love to see your personality come through.
Showcase Your Technical Skills: In your application, be specific about the tools and technologies you’ve worked with. Whether it’s CI/CD pipelines or model monitoring, we want to know what you bring to the table. Don’t hold back on the details!
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’s super easy – just a few clicks and you’re done!
How to prepare for a job interview at CMC Markets UK Plc
✨Know Your ML Ops Inside Out
Make sure you brush up on your knowledge of machine learning operations. Understand the lifecycle of ML models, from training to deployment, and be ready to discuss specific tools and frameworks you've used. This will show that you're not just familiar with the theory but have practical experience too.
✨Showcase Your Problem-Solving Skills
Prepare to discuss real-world challenges you've faced in previous roles, especially around reliability and scalability of ML systems. Use the STAR method (Situation, Task, Action, Result) to structure your answers, making it easy for interviewers to see how you approach problem-solving.
✨Familiarise Yourself with CI/CD Pipelines
Since this role involves designing CI/CD pipelines for ML, make sure you can talk about your experience with continuous integration and deployment. Be ready to explain how you've implemented these processes in past projects and the impact they had on model performance and reliability.
✨Ask Insightful Questions
Interviews are a two-way street, so prepare some thoughtful questions about the company's ML infrastructure and their approach to model monitoring. This not only shows your interest in the role but also helps you gauge if the company is the right fit for you.