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- Tasks: Support major projects in Backup Engineering using Python and Machine Learning.
- Company: Join a leading financial services client in Glasgow with a hybrid work model.
- Benefits: Competitive day rate, flexible working, and a chance to enhance your skills.
- Other info: Opportunity for career growth in a dynamic and collaborative environment.
- Why this job: Make an impact on innovative projects while developing your expertise in ML and Python.
- Qualifications: Strong Python programming and Machine Learning experience required.
Harvey Nash's FS Client have a requirement for a Python ML Engineer, you will support the team in delivering 2 major projects in the Backup Engineering team. Strong Python and Machine Learning experience is key.
Required Skills:
- Excellent programming skills with Python
- Strong experience with message queues (Kafka/RabbitMQ/Celery/etc)
- Strong experience creating REST API servers
- Strong experience with ML
- Excellent ability to debug complex and novel issues, understanding the need to go beyond the documentation
- Excellent analytical skills, capable of fast decision making using sound judgement, and not afraid to explore new ideas
- Excellent interpersonal skills in dealing with customers with differing technical specializations
- Good organizational and English communication skills are required, including prioritization of multiple projects and objectives
Desirable Skills:
- Experience of backup and data protection platforms, in particular Veritas NetBackup
- Understanding of data deduplication technology
- Systems administration experience in UNIX and/or Windows Server environments
- Experience in other areas of storage SAN, NAS, S3 object storage
- Experience with Kubernetes or OpenShift
- Experience with Perl
Python ML Engineer employer: Harvey Nash
Contact Detail:
Harvey Nash Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Python ML Engineer
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, attend meetups, and engage in online forums. 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 and ML projects. This is your chance to demonstrate your expertise beyond just a CV. Make sure to include links to any relevant GitHub repositories or personal projects.
✨Tip Number 3
Prepare for interviews by practising common technical questions related to Python and machine learning. We recommend doing mock interviews with friends or using online platforms to get comfortable with the format.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, we often have exclusive roles listed that you won’t find anywhere else. Don’t miss out!
We think you need these skills to ace Python ML Engineer
Some tips for your application 🫡
Show Off Your Python Skills: Make sure to highlight your programming prowess in Python right from the get-go. We want to see how you've used Python in real projects, especially in machine learning contexts. Don't just list skills; give us examples!
Talk About Your ML Experience: Since this role is all about machine learning, share specific projects where you've implemented ML techniques. We love seeing how you’ve tackled complex problems and what tools you used to achieve success.
Demonstrate Your Problem-Solving Skills: We’re looking for someone who can debug tricky issues and think outside the box. Share a story or two about challenges you've faced and how you overcame them. This will show us your analytical skills in action!
Keep It Organised and Clear: When writing your application, clarity is key! Make sure your communication is straightforward and well-structured. We appreciate good organisation, so don’t hesitate to prioritise your experiences and skills effectively.
How to prepare for a job interview at Harvey Nash
✨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 in machine learning. Practising coding challenges can also help you demonstrate your programming prowess.
✨Familiarise Yourself with Message Queues
Since experience with message queues like Kafka or RabbitMQ is crucial, take some time to understand how they work. Be prepared to explain how you've implemented these technologies in previous roles and how they can enhance data processing in ML applications.
✨Show Off Your Debugging Skills
Prepare to discuss complex issues you've debugged in the past. Think of specific examples where you went beyond documentation to solve a problem. This will showcase your analytical skills and ability to tackle novel challenges.
✨Communicate Clearly and Confidently
Strong interpersonal skills are key for this role. Practice explaining technical concepts in simple terms, as you'll likely need to communicate with team members from various backgrounds. Good communication can set you apart from other candidates.