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- Tasks: Design and implement MLOps best practices for machine learning models.
- Company: Leading UK insurance company with a focus on innovation.
- Benefits: Competitive salary up to £80,000 and comprehensive benefits.
- Why this job: Join a dynamic team and shape the future of machine learning in insurance.
- Qualifications: Experience in MLOps and collaboration with Data Scientists and Engineers.
- Other info: Exciting opportunity for career growth in a supportive environment.
The predicted salary is between 48000 - 64000 £ per year.
A leading insurance company in the UK is seeking a Machine Learning Engineer to join their Transversal Data team. The successful candidate will design and implement MLOps best practices while maintaining the infrastructure for machine learning models.
Responsibilities include:
- Collaborating with Data Scientists and Engineers
- Defining best practices
- Contributing to knowledge sharing
A competitive salary of up to £80,000 along with comprehensive benefits is offered, making this an exciting opportunity for professionals in the field.
MLOps Engineer — Production ML on Azure in Redhill employer: AXA Group
Contact Detail:
AXA Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land MLOps Engineer — Production ML on Azure in Redhill
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those already working in MLOps or at the company you're eyeing. A friendly chat can open doors and give you insights that a job description just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your MLOps projects, especially any work with Azure. This is your chance to demonstrate your expertise and passion for the field, so make it shine!
✨Tip Number 3
Prepare for the interview by brushing up on common MLOps scenarios. Think about how you'd tackle real-world problems and be ready to discuss your thought process. We want to see how you approach challenges!
✨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 take that extra step to connect with us directly.
We think you need these skills to ace MLOps Engineer — Production ML on Azure in Redhill
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the MLOps Engineer role. Highlight your experience with Azure and any relevant projects you've worked on. We want to see how your skills align with our needs!
Showcase Your Collaboration Skills: Since you'll be working closely with Data Scientists and Engineers, it's important to showcase your teamwork abilities. Include examples of past collaborations in your application to show us you're a team player.
Highlight Best Practices Knowledge: We’re keen on MLOps best practices, so don’t forget to mention any frameworks or methodologies you’ve implemented. This will help us see your expertise in maintaining ML infrastructure.
Apply Through Our Website: For the best chance of success, apply directly through our website. It’s the easiest way for us to review your application and get back to you quickly!
How to prepare for a job interview at AXA Group
✨Know Your MLOps Inside Out
Make sure you brush up on MLOps best practices, especially in the context of Azure. Be ready to discuss how you've implemented these practices in previous roles and how they can benefit the insurance company.
✨Collaborate Like a Pro
Since you'll be working closely with Data Scientists and Engineers, prepare examples of successful collaborations from your past. Highlight how you contributed to knowledge sharing and defined best practices in those situations.
✨Showcase Your Problem-Solving Skills
Be prepared to tackle hypothetical scenarios during the interview. Think about challenges you might face in maintaining ML infrastructure and how you would approach solving them. This will demonstrate your critical thinking and technical prowess.
✨Ask Insightful Questions
Interviews are a two-way street! Prepare thoughtful questions about the company's data strategy, team dynamics, and future projects. This shows your genuine interest in the role and helps you assess if it's the right fit for you.
