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- Tasks: Build and maintain ML tools and deployment frameworks in a collaborative environment.
- Company: Dynamic financial services business based in Manchester.
- Benefits: Competitive salary plus bonus, with opportunities for growth.
- Why this job: Join a team that values innovation and engineering best practices in ML.
- Qualifications: Strong Python skills and experience in data science or ML Ops.
- Other info: Exciting opportunity to work in the fast-paced financial sector.
The predicted salary is between 36000 - 60000 £ per year.
A financial services business in Manchester is seeking a Machine Learning Engineer to build and maintain ML tooling and deployment frameworks. The role emphasizes collaborative work with data teams and the importance of engineering best practices. Ideal candidates have strong Python skills and experience in data science or ML Ops, particularly in financial services. The position offers a competitive salary plus bonus.
ML Engineer, Financial Services — Scale & Automate ML in Manchester employer: Miryco Consultants Ltd
Contact Detail:
Miryco Consultants Ltd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land ML Engineer, Financial Services — Scale & Automate ML in Manchester
✨Tip Number 1
Network like a pro! Reach out to folks in the financial services sector, especially those working with ML. A friendly chat can open doors and give you insights that job descriptions just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your ML projects, especially those relevant to finance. This is your chance to demonstrate your Python prowess and engineering best practices in action.
✨Tip Number 3
Prepare for technical interviews by brushing up on your ML concepts and coding challenges. Practise explaining your thought process clearly; collaboration is key in this role, so show us how you work with others!
✨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 ML Engineer, Financial Services — Scale & Automate ML in Manchester
Some tips for your application 🫡
Show Off Your Python Skills: Make sure to highlight your strong Python skills in your application. We want to see how you've used Python in your previous projects, especially in the context of ML tooling and deployment frameworks.
Emphasise Collaboration: Since this role involves working closely with data teams, don’t forget to mention any collaborative projects you've been part of. We love seeing how you’ve worked with others to achieve common goals!
Highlight Your Experience in Financial Services: If you've got experience in financial services, make it a focal point in your application. We’re looking for candidates who understand the unique challenges and opportunities in this sector.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at Miryco Consultants Ltd
✨Know Your Python Inside Out
Since the role requires strong Python skills, make sure you brush up on your coding abilities. Be prepared to discuss your experience with Python libraries commonly used in ML, like NumPy and Pandas, and maybe even solve a coding challenge during the interview.
✨Showcase Your ML Ops Experience
Highlight any previous work you've done in ML Ops, especially in financial services. Be ready to discuss specific projects where you built or maintained ML tooling and deployment frameworks, as this will demonstrate your hands-on experience and understanding of the field.
✨Emphasise Collaboration
This role involves working closely with data teams, so be prepared to talk about your collaborative experiences. Share examples of how you've worked in teams, resolved conflicts, or contributed to group projects, showcasing your ability to communicate effectively.
✨Understand Engineering Best Practices
Familiarise yourself with engineering best practices relevant to ML. Be ready to discuss how you ensure code quality, maintainability, and scalability in your projects. This shows that you not only know how to build models but also how to do it efficiently and sustainably.
