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- Tasks: Build and deploy scalable ML systems in a collaborative, innovative environment.
- Company: Leading tech recruitment company in the UK with a focus on cutting-edge technology.
- Benefits: Flexible work environment and opportunities for professional growth.
- Why this job: Join a team that values innovation and collaboration in machine learning.
- Qualifications: 3-5 years of ML engineering experience and a Master’s or PhD in a numerate discipline.
- Other info: Work in cross-functional teams to develop cloud-native infrastructure.
The predicted salary is between 48000 - 72000 £ per year.
A leading technology recruitment company in the UK is seeking a Senior Machine Learning Engineer to build and deploy scalable ML systems. The ideal candidate will have 3-5 years of experience in machine learning engineering and a Master’s or PhD in a numerate discipline. You will work in cross-functional teams to develop cloud-native infrastructure and ensure best practices in model deployment. This role offers a flexible work environment with a focus on innovation and collaboration.
Senior ML Engineer – Production ML, MLOps, Hybrid employer: Xcede
Contact Detail:
Xcede Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior ML Engineer – Production ML, MLOps, Hybrid
✨Tip Number 1
Network like a pro! Reach out to your connections in the tech industry, especially those in ML and MLOps. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your best ML projects. Whether it’s GitHub repos or a personal website, let your work speak for itself and make it easy for recruiters to see what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice common ML scenarios and be ready to discuss how you’ve tackled challenges in past projects. We want to see your problem-solving skills in action!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Senior ML Engineer – Production ML, MLOps, Hybrid
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in machine learning engineering and any relevant projects you've worked on. We want to see how your skills align with the role, so don’t be shy about showcasing your achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about ML 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 technical expertise, especially in MLOps and cloud-native infrastructure. We’re looking for someone who can hit the ground running, so highlight any relevant tools or technologies you’ve used.
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!
How to prepare for a job interview at Xcede
✨Know Your ML Fundamentals
Brush up on your machine learning concepts and algorithms. Be ready to discuss your experience with different models, their applications, and the challenges you've faced in deploying them. This will show your depth of knowledge and practical experience.
✨Showcase Your MLOps Skills
Prepare to talk about your experience with MLOps practices. Highlight any tools or frameworks you've used for model deployment and monitoring. Discuss how you ensure scalability and reliability in production environments, as this is crucial for the role.
✨Collaboration is Key
Since you'll be working in cross-functional teams, be ready to share examples of how you've collaborated with others. Discuss how you communicate complex technical concepts to non-technical team members and how you handle feedback and differing opinions.
✨Ask Insightful Questions
Prepare thoughtful questions about the company's approach to innovation and collaboration. Inquire about their current projects and challenges in ML deployment. This shows your genuine interest in the role and helps you assess if it's the right fit for you.
