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- Tasks: Design scalable automation solutions and develop REST APIs with a global tech team.
- Company: Join McGregor Recruitment, a leader in enterprise technology.
- Benefits: Competitive day rate of £450 PAYE and flexible onsite work.
- Other info: Collaborate with engineering teams and grow your career in Glasgow.
- Why this job: Make an impact in a dynamic environment while honing your Python and ML skills.
- Qualifications: Strong Python skills and experience with machine learning and REST services.
The predicted salary is between 117000 - 117000 £ per year.
McGregor Recruitment seeks an experienced Python ML Engineer to join a global enterprise technology team in Glasgow. In this onsite role (3 days per week), you will focus on designing scalable automation solutions, collaborating with engineering teams to implement workload orchestration, and developing REST APIs.
The ideal candidate should have strong Python skills and experience with machine learning, REST services, and message queue technologies like Kafka or RabbitMQ.
This position offers a competitive day rate of £450 PAYE.
Python ML Engineer — Automation & REST APIs employer: McGregor Recruitment
Contact Detail:
McGregor Recruitment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Python ML Engineer — Automation & REST APIs
✨Tip Number 1
Network like a pro! Reach out to your connections in the tech industry, especially those who work with Python or machine learning. 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, especially those involving ML and REST APIs. This gives potential employers a sneak peek into your coding style and problem-solving abilities.
✨Tip Number 3
Prepare for technical interviews by brushing up on your Python and ML concepts. Practice coding challenges and be ready to discuss your past projects. We all know that confidence is key, so get comfortable with your knowledge!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who take the initiative to connect directly with us.
We think you need these skills to ace Python ML Engineer — Automation & REST APIs
Some tips for your application 🫡
Show Off Your Python Skills: Make sure to highlight your Python expertise in your application. We want to see how you've used Python in real projects, especially in machine learning and automation. Don't hold back on those details!
Tailor Your Application: Take a moment to customise your application for this role. Mention your experience with REST APIs and any message queue technologies like Kafka or RabbitMQ. We love seeing how your background fits with what we're looking for!
Be Clear and Concise: When writing your application, keep it straightforward. We appreciate clarity, so avoid jargon and get straight to the point about your skills and experiences. This helps us understand your fit for the role quickly.
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. Plus, we love seeing applications come in through our own platform!
How to prepare for a job interview at McGregor Recruitment
✨Know Your Python Inside Out
Make sure you brush up on your Python skills before the interview. Be ready to discuss your experience with Python in detail, especially in relation to machine learning and REST APIs. Practising coding challenges can help you demonstrate your proficiency.
✨Showcase Your ML Projects
Prepare to talk about specific machine learning projects you've worked on. Highlight the challenges you faced, the solutions you implemented, and the impact of your work. This will show your practical experience and problem-solving skills.
✨Understand Automation and Orchestration
Since the role involves designing scalable automation solutions, be prepared to discuss your understanding of workload orchestration. Familiarise yourself with tools and frameworks that facilitate automation, and be ready to share examples of how you've used them.
✨Familiarity with Message Queues
Brush up on your knowledge of message queue technologies like Kafka or RabbitMQ. Be ready to explain how you've used these technologies in past projects, as this will demonstrate your ability to handle data flow in distributed systems.