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- Tasks: Design and develop innovative solutions using Python and machine learning for data protection.
- Company: Join a global leader in wealth and investment management known for tech innovation.
- Benefits: Competitive salary, ongoing support, and professional development opportunities.
- Other info: Dynamic role with potential for permanent employment and career growth.
- Why this job: Revolutionise data handling and make a real impact with cutting-edge technology.
- Qualifications: Expertise in Python, machine learning, and experience with distributed systems required.
The predicted salary is between 60000 - 80000 £ per year.
We are seeking a Senior Engineer for a global leader in wealth and investment management known for its commitment to excellence and technological innovation. This firm manages a vast, complex infrastructure where data integrity is paramount. The role is a key strategic hire within the Infrastructure Engineering team, aimed at revolutionizing how the firm handles data protection and workload automation through machine learning and advanced backend engineering.
Role Overview
You will serve as a Senior Engineer focused on building a sophisticated abstraction layer for backup applications, automating complex workload placements and delivering a seamless self-service experience via REST APIs.
Key Responsibilities
- System Design: Architect and deploy scalable, reliable solutions that bridge the gap between modern tech stacks and essential legacy infrastructure.
- Intelligent Automation: Leverage Machine Learning to optimize backup processes and automate workload placement across the enterprise.
- Stakeholder Engagement: Act as a technical consultant to internal SMEs across storage, database, and UNIX domains to define future‑state migration paths.
- API Development: Develop and maintain robust REST API servers to enable self-service capabilities for a diverse end-user base.
Required Skills
- Python Mastery: Exceptional programming skills with a focus on building complex, enterprise‑grade applications.
- Distributed Systems: Strong experience with message queuing architectures such as Kafka, RabbitMQ, or Celery.
- Machine Learning: Proven expertise in ML implementation to solve real-world automation and optimization problems.
- Advanced Debugging: The ability to navigate and resolve novel, undocumented technical issues through sound judgment and deep system knowledge.
- Infrastructure Depth: Experience with storage platforms (SAN, NAS, S3), data deduplication, or Veritas NetBackup.
- Modern Platforms: Hands‑on experience with Kubernetes, OpenShift, or general UNIX/Windows systems administration.
- Polyglot Programming: Familiarity with Perl is a plus.
Closing & The mthree Model
These roles are delivered via the mthree Expert programme. As a consultant, you will be directly employed by mthree and deployed exclusively to this single prestigious client. You will receive ongoing support and professional development, with the majority of our consultants eventually converting to permanent employees with the client.
Python ML Engineer in Glasgow employer: mthree
Contact Detail:
mthree 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 folks in the industry on LinkedIn or at meetups. We all know that sometimes it’s not just what you know, but who you know that can get your foot in the door.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your Python projects, especially those involving machine learning and automation. We want to see what you can do, so make it easy for potential employers to check out your work.
✨Tip Number 3
Prepare for interviews by practising common technical questions and coding challenges. We recommend using platforms like LeetCode or HackerRank to sharpen your skills. The more prepared you are, the more confident you'll feel!
✨Tip Number 4
Apply through our website! We’ve got loads of opportunities waiting for you, and applying directly can sometimes give you an edge. Plus, we’re here to support you every step of the way!
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 is tailored to the role of Python ML Engineer. Highlight your experience with Python, machine learning, and any relevant projects that showcase your skills in building complex applications.
Craft a Compelling Cover Letter: Your cover letter should tell us why you're the perfect fit for this role. Share your passion for data protection and automation, and how your background aligns with our mission to innovate in wealth and investment management.
Showcase Your Technical Skills: Don’t just list your skills; demonstrate them! Include specific examples of how you've used Python, worked with distributed systems, or implemented machine learning solutions in past roles.
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. This way, we can easily track your application and get back to you quicker!
How to prepare for a job interview at mthree
✨Master the Tech Stack
Make sure you’re well-versed in Python and the specific technologies mentioned in the job description, like Kafka or Kubernetes. Brush up on your knowledge of distributed systems and be ready to discuss how you've used these tools in past projects.
✨Showcase Your ML Expertise
Prepare to talk about your experience with machine learning, especially in relation to automation and optimisation. Have examples ready that demonstrate how you've implemented ML solutions to solve real-world problems, as this will be crucial for the role.
✨Engage with Stakeholders
Since stakeholder engagement is key, think about how you’ve collaborated with different teams in previous roles. Be ready to share specific instances where you acted as a technical consultant and how you navigated complex discussions around system design.
✨API Development Insights
Familiarise yourself with REST API development, as it’s a significant part of the role. Prepare to discuss any relevant projects where you’ve built or maintained APIs, focusing on how you ensured a seamless self-service experience for users.