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 opportunities.
- 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 required.
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 employer: Talenzon group
Join a dynamic team in 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 in a city renowned for its tech scene, while contributing to impactful projects that shape the future of AI.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer – Production AI Systems
✨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 help you land that Machine Learning Engineer role.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects. We recommend including links to GitHub repos or any live demos. This way, potential employers can see your work in action!
✨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. We suggest doing mock interviews to build confidence.
✨Tip Number 4
Apply through our website! We make it super easy to find and apply for roles like the Machine Learning Engineer position. Plus, it shows you’re genuinely interested in joining our team!
We think you need these skills to ace Machine Learning Engineer – Production AI Systems
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience in deploying and scaling machine learning models. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re passionate about machine learning and how your background makes you a perfect fit for our team. Keep it engaging and personal.
Showcase Your Technical Skills:Since we’re looking for someone with strong technical expertise, be sure to mention your proficiency in Python, cloud platforms, and any experience with Docker or Kubernetes. We love seeing those skills in action!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re serious about joining our team!
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 reliability and scalability in production environments.
✨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 talk about specific services you’ve used for deploying ML models and how they contributed to your projects.
✨Showcase Your Collaboration Skills
This role requires collaboration with data scientists, so be ready to share examples of how you’ve worked in teams. Discuss how you’ve communicated technical concepts to non-technical stakeholders and how you’ve integrated feedback into your work.
