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- Tasks: Design and develop scalable automation solutions using Python and machine learning.
- Company: Join a leading global enterprise in financial services.
- Benefits: Competitive day rate, onsite collaboration, and opportunities for professional growth.
- Other info: Collaborate with cross-functional teams and tackle complex technical challenges.
- Why this job: Make an impact by shaping future technology architecture in a dynamic environment.
- Qualifications: Strong Python skills and experience with machine learning and REST APIs.
The predicted salary is between 31500 - 45000 £ per year.
We are seeking an experienced Python ML Engineer to join a global enterprise technology team supporting critical infrastructure and automation initiatives within a leading financial services environment.
In this role, you will design and develop scalable automation solutions focused on workload orchestration, backup abstraction, and self-service capabilities delivered through REST APIs. You will collaborate closely with cross-functional engineering teams and subject matter experts across backup, storage, database, and UNIX environments to help shape future-state architecture and migration strategies.
The ideal candidate will have strong Python development expertise combined with experience building reliable, enterprise-grade applications using modern technology stacks. You should be comfortable working in both greenfield and legacy environments and capable of solving complex technical challenges independently.
Key requirements include:
- Strong Python programming skills
- Experience with machine learning technologies
- Hands-on experience with message queue technologies such as Kafka, RabbitMQ, or Celery
- Proven ability to build REST API services
- Excellent debugging and analytical problem-solving skills
Python ML Engineer in Glasgow employer: McGregor Boyall Associates
Contact Detail:
McGregor Boyall Associates Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Python ML Engineer in Glasgow
✨Tip Number 1
Network like a pro! Reach out to your connections in the tech industry, especially those in financial services. A friendly chat can lead to insider info about job openings that aren't even advertised yet.
✨Tip Number 2
Show off your skills! Create a GitHub repository showcasing your Python projects and any machine learning models you've built. This gives potential employers a taste of what you can do beyond your CV.
✨Tip Number 3
Prepare for technical interviews by brushing up on your debugging skills and understanding REST APIs inside out. Practise common coding challenges and be ready to explain your thought process during problem-solving.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities, and applying directly can sometimes give you an edge. Plus, it’s super easy to keep track of your applications with us.
We think you need these skills to ace Python ML Engineer in Glasgow
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your Python programming skills and experience with machine learning technologies. We want to see how your background aligns 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 excited about the Python ML Engineer position and how your experience with REST APIs and message queue technologies makes you a great fit for our team.
Showcase Problem-Solving Skills: In your application, give examples of complex technical challenges you've tackled in the past. We love seeing how you approach problems, especially in both greenfield and legacy environments!
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 don’t miss out on any important updates from our team!
How to prepare for a job interview at McGregor Boyall Associates
✨Know Your Python Inside Out
Make sure you brush up on your Python skills before the interview. Be ready to discuss your past projects and how you've used Python to solve complex problems, especially in machine learning contexts. Practising coding challenges can also help you demonstrate your expertise.
✨Familiarise Yourself with ML Technologies
Since the role requires experience with machine learning technologies, take some time to review key concepts and tools. Be prepared to talk about any ML projects you've worked on, the algorithms you used, and the outcomes. This will show your depth of knowledge and practical experience.
✨Understand REST APIs and Message Queues
Get comfortable discussing REST API services and message queue technologies like Kafka or RabbitMQ. You might be asked to explain how you’ve implemented these in previous roles, so having specific examples ready will help you stand out.
✨Show Your Problem-Solving Skills
Be ready to tackle some technical challenges during the interview. Think of examples where you've debugged issues or solved complex problems independently. This will highlight your analytical skills and ability to work under pressure, which are crucial for this role.