At a Glance
- Tasks: Deploy and scale machine learning models, ensuring they work seamlessly in real-world applications.
- Company: Join a leading tech firm in London focused on innovative AI solutions.
- Benefits: Competitive salary, hands-on experience, and opportunities for professional growth.
- Other info: Dynamic team environment with exciting projects and career advancement potential.
- Why this job: Make an impact by transforming cutting-edge ML models into reliable production systems.
- Qualifications: Strong ML engineering skills, Python proficiency, and cloud platform experience.
The predicted salary is between 60000 - 80000 £ per year.
We are looking for a Machine Learning Engineer with strong experience in deploying and scaling machine learning models to join our client’s on-site team in London. This role focuses on taking machine learning models from experimentation to production, ensuring they are scalable, reliable, and integrated into real-world applications.
- Deploy and maintain machine learning models in production environments
- Build and optimise data pipelines for training and inference workflows
- Collaborate with data scientists to productionise models
- Monitor model performance and implement retraining pipelines
- Improve scalability, latency, and reliability of ML systems
- Integrate ML services into backend applications via APIs
- Implement MLOps best practices across the ML lifecycle
Required Skills & Experience
- Strong experience in machine learning engineering or applied ML
- Proficiency in Python and ML frameworks
- Experience with cloud platforms such as Amazon Web Services, Google Cloud, or Microsoft Azure
- Experience with containerisation using Docker and orchestration via Kubernetes
- Experience with model deployment and monitoring
Nice to Have
- Experience with MLOps tools and pipelines
- Familiarity with feature stores and model versioning
- Experience with real-time inference systems
Machine Learning Engineer – Production AI Systems in London employer: Talenzon group
Join a dynamic team in the heart of London as a Machine Learning Engineer, where innovation meets collaboration. Our company fosters a vibrant work culture that prioritises employee growth through continuous learning opportunities and hands-on experience with cutting-edge technologies. Enjoy the unique advantage of working on impactful projects in a thriving city, all while being part of a supportive environment that values your contributions and encourages professional development.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer – Production AI Systems in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with fellow Machine Learning Engineers. 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 machine learning projects. Whether it's a GitHub repo or a personal website, having tangible examples of your work can really set you apart from the competition.
✨Tip Number 3
Prepare for those interviews! Brush up on your technical knowledge and be ready to discuss your experience with deploying models and using cloud platforms. Practising common interview questions can help you feel more confident.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities waiting for talented Machine Learning Engineers like you. Plus, applying directly can sometimes give you a better chance at landing that dream job.
We think you need these skills to ace Machine Learning Engineer – Production AI Systems in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience in deploying and scaling machine learning models. Use keywords from the job description to show we’re on the same page about what you bring to the table.
Showcase Your Projects:Include specific examples of projects where you've implemented MLOps best practices or worked with cloud platforms. We love seeing real-world applications of your skills!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Explain why you're passionate about machine learning and how your experience aligns with our needs. Keep it engaging and personal.
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 don’t miss any important updates from us!
How to prepare for a job interview at Talenzon group
✨Know Your Models Inside Out
Make sure you can discuss the machine learning models you've worked on in detail. Be ready to explain how you deployed them, the challenges you faced, and how you optimised their performance. This shows your hands-on experience and understanding of the entire ML lifecycle.
✨Brush Up on MLOps Best Practices
Since this role involves implementing MLOps, it’s crucial to be familiar with best practices in model deployment and monitoring. Prepare to discuss tools and pipelines you’ve used, and how you ensure scalability and reliability in production environments.
✨Showcase Your Collaboration Skills
Collaboration is key in this role, so think of examples where you’ve worked closely with data scientists or other teams. Highlight how you contributed to productionising models and integrating ML services into applications, as this will demonstrate your teamwork abilities.
✨Get Comfortable with Cloud Platforms
Familiarise yourself with the cloud platforms mentioned in the job description, like AWS, Google Cloud, or Azure. Be prepared to discuss your experience with these platforms, especially in relation to deploying and scaling ML models, as this is a critical aspect of the role.
