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- Tasks: Develop and maintain machine learning models while collaborating with analysts.
- Company: Dynamic financial services consulting firm based in London.
- Benefits: Competitive salary, discretionary bonus scheme, and healthcare access.
- Why this job: Join a cutting-edge team and work on impactful machine learning projects.
- Qualifications: Strong Python skills and experience in CI/CD required.
- Other info: Hybrid role with opportunities for professional growth.
The predicted salary is between 36000 - 60000 £ per year.
A financial services consulting company seeks a Machine Learning Operations Engineer to develop and maintain machine learning models in London. This hybrid role involves collaborating with analysts, deploying models using Azure ML, and managing large datasets.
Ideal candidates should have:
- Strong Python skills
- Experience in CI/CD
- Ability to communicate technical concepts effectively
The position offers a competitive benefits package including a discretionary bonus scheme and healthcare access.
MLOps Engineer: Azure ML & Data Pipelines (Hybrid) employer: Proactive.IT Appointments
Contact Detail:
Proactive.IT Appointments Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land MLOps Engineer: Azure ML & Data Pipelines (Hybrid)
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. 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, especially those involving Azure ML and data pipelines. This will give potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on your Python and CI/CD knowledge. Practice explaining your past projects and how you tackled challenges, as this will help you communicate effectively during technical discussions.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might just be the perfect fit for you. Plus, it’s a great way to get noticed by our hiring team.
We think you need these skills to ace MLOps Engineer: Azure ML & Data Pipelines (Hybrid)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your Python skills and experience with CI/CD. We want to see how your background aligns with the MLOps 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 excited about the role and how your experience with Azure ML can benefit us. Keep it concise but impactful!
Showcase Your Communication Skills: Since this role involves collaborating with analysts, it’s important to demonstrate your ability to communicate technical concepts clearly. We love candidates who can bridge the gap between tech and non-tech folks!
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 Proactive.IT Appointments
✨Know Your Tech Inside Out
Make sure you brush up on your Python skills and Azure ML knowledge. Be ready to discuss specific projects where you've deployed models or managed data pipelines. The more you can demonstrate your technical expertise, the better!
✨Showcase Your Collaboration Skills
Since this role involves working closely with analysts, be prepared to share examples of how you've successfully collaborated in the past. Highlight any experiences where you communicated complex technical concepts to non-technical team members.
✨Understand CI/CD Processes
Familiarise yourself with Continuous Integration and Continuous Deployment practices. Be ready to explain how you've implemented these processes in previous roles, as this will show your ability to streamline model deployment effectively.
✨Prepare Questions for Them
Interviews are a two-way street! Think of insightful questions about their current projects or challenges they face in machine learning operations. This shows your genuine interest in the role and helps you assess if it's the right fit for you.
