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- Tasks: Build and deploy real-world AI systems while collaborating with data science teams.
- Company: Leading recruitment agency in the UK with a focus on innovation.
- Benefits: Salary up to £85k, mentorship opportunities, and impactful projects.
- Why this job: Make a real difference in financial and professional services with cutting-edge AI.
- Qualifications: Proven machine learning experience, Python proficiency, and Docker/Kubernetes skills.
- Other info: Great opportunity for career growth and mentoring junior engineers.
The predicted salary is between 51000 - 85000 £ per year.
A leading recruitment agency in the UK is seeking a Machine Learning Engineer to build and deploy impactful AI systems. You will collaborate with data science teams, design cloud-native systems, and mentor junior engineers.
The ideal candidate has proven experience in machine learning, is proficient in Python, and has hands-on experience with Docker and Kubernetes.
This role offers a salary of up to £85k and the opportunity to make a real impact in financial and professional services.
ML Engineer I & II: Build & Deploy Real-World AI employer: Xcede Recruitment Solutions
Contact Detail:
Xcede Recruitment Solutions Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land ML Engineer I & II: Build & Deploy Real-World AI
✨Tip Number 1
Network like a pro! Reach out to your connections in the AI and machine learning space. Attend meetups or webinars, and don’t be shy about asking for introductions. You never know who might have the inside scoop on job openings!
✨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, make sure potential employers can see what you can do with Python, Docker, and Kubernetes.
✨Tip Number 3
Prepare for those interviews! Brush up on common ML concepts and be ready to discuss your past experiences. Practice coding challenges and system design questions that are relevant to building cloud-native systems.
✨Tip Number 4
Apply through our website! We’ve got loads of opportunities waiting for you. Tailor your application to highlight your experience in machine learning and your ability to mentor others. Let’s get you that dream job!
We think you need these skills to ace ML Engineer I & II: Build & Deploy Real-World AI
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in machine learning and your proficiency in Python. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about AI and how you can contribute to our team. We love seeing enthusiasm and a clear understanding of the role.
Showcase Your Technical Skills: Don’t forget to mention your hands-on experience with Docker and Kubernetes. We’re looking for someone who can hit the ground running, so any specific examples of your work with these tools will definitely catch our eye!
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 Xcede Recruitment Solutions
✨Know Your ML Fundamentals
Brush up on your machine learning concepts and algorithms. Be ready to discuss your previous projects and how you applied these principles. This shows that you not only understand the theory but can also implement it in real-world scenarios.
✨Showcase Your Python Skills
Since proficiency in Python is key for this role, prepare to demonstrate your coding skills. You might be asked to solve a problem on the spot, so practice common algorithms and data structures in Python beforehand.
✨Familiarise Yourself with Docker and Kubernetes
Hands-on experience with Docker and Kubernetes is essential. Be prepared to discuss how you've used these tools in past projects, and consider bringing examples of how you've deployed applications using them.
✨Prepare for Team Collaboration Questions
As you'll be collaborating with data science teams and mentoring junior engineers, expect questions about teamwork and leadership. Think of specific examples where you've successfully worked in a team or guided others, and be ready to share those stories.
