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- Tasks: Design and build Python services to automate workflows and enhance decision-making.
- Company: Join a global tech team modernising large-scale technology estates.
- Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
- Other info: Collaborate with experts and tackle exciting technical challenges in a dynamic setting.
- Why this job: Make a real impact by solving complex engineering challenges with cutting-edge tech.
- Qualifications: Strong Python skills and experience with machine learning in production environments.
The predicted salary is between 50000 - 65000 £ per year.
Are you a Python specialist who enjoys solving complex engineering challenges at scale? I am looking for an experienced Python Machine Learning Engineer based in Scotland to help modernise and automate a large-scale technology estate. You'll be part of an international team building intelligent services that simplify infrastructure, improve resilience and enable self-service through well-designed APIs.
What you'll be working on:
- Designing and building robust Python services that automate complex workflows
- Developing API-driven solutions that abstract underlying platforms and enable self-service
- Applying machine learning techniques to enhance automation and decision-making
- Integrating modern tooling with legacy technologies where required
- Partnering with subject matter experts across storage, backup, databases and UNIX environments to shape future-state solutions
- Troubleshooting and resolving technically challenging issues that go beyond standard documentation
What you'll bring:
- Strong Python development experience in production environments
- Hands-on expertise with message-driven architectures (e.g. Kafka, RabbitMQ, Celery or similar)
- Proven experience building and maintaining RESTful APIs
- Solid experience applying machine learning in real-world systems
- Confidence debugging complex, unfamiliar problems with a pragmatic mindset
- Strong communication skills and the ability to explain technical solutions to varied audiences
- The ability to juggle multiple priorities in a fast-paced environment
Nice to have (but not essential):
- Exposure to enterprise backup or data protection platforms
- Knowledge of data deduplication concepts
- Systems administration experience across UNIX and/or Windows
- Familiarity with storage technologies (SAN, NAS, object storage)
- Experience with container platforms such as Kubernetes or OpenShift
- Working knowledge of Perl
This is a chance to join a global team where your work will underpin their critical platforms used across a large, regulated environment. Interested? Apply now for immediate consideration.
Python ML Engineer in Central employer: Henderson Scott
Contact Detail:
Henderson Scott Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Python ML Engineer in Central
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, attend meetups, and engage with online communities. 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 Python projects, especially those involving machine learning and APIs. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice explaining your past projects and how you tackled complex challenges, as this will help you shine during those crucial conversations.
✨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 Python ML Engineer in Central
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your Python development experience and any machine learning projects you've worked on. We want to see how your skills match the job description, so don’t be shy about showcasing your relevant expertise!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about Python and machine learning. Share specific examples of how you've tackled complex engineering challenges in the past – we love a good story!
Show Off Your Communication Skills: Since you'll be working with various teams, it's important to demonstrate your ability to explain technical concepts clearly. In your application, mention instances where you've successfully communicated complex ideas to non-technical audiences.
Apply Through Our Website: We encourage you to apply directly through our website for the best chance of getting noticed. It’s super easy, and you’ll be one step closer to joining our international team of tech enthusiasts!
How to prepare for a job interview at Henderson Scott
✨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 production environments and be prepared to solve coding challenges on the spot. Practising common algorithms and data structures can really help you shine.
✨Showcase Your Machine Learning Experience
Be ready to talk about how you've applied machine learning techniques in real-world systems. Prepare examples of projects where you've enhanced automation or decision-making using ML, and be specific about the tools and frameworks you used.
✨Understand API-Driven Solutions
Since you'll be developing API-driven solutions, make sure you can explain how RESTful APIs work and share any relevant experiences. Discuss any message-driven architectures you've worked with, like Kafka or RabbitMQ, and how they fit into your projects.
✨Communicate Clearly and Confidently
Strong communication skills are key, especially when explaining technical solutions to non-technical audiences. Practice articulating complex concepts in simple terms, and be ready to demonstrate your ability to troubleshoot and resolve challenging issues.