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- Tasks: Lead AI initiatives and develop multi-agent systems in Risk Technology.
- Company: Top global financial services provider based in Scotland.
- Benefits: Innovative work environment with opportunities for career advancement.
- Why this job: Make a real impact in asset and wealth management risk with cutting-edge technology.
- Qualifications: Relevant degree, extensive ML engineering experience, and proficiency in Python and AWS.
- Other info: Collaborate with diverse teams to enhance business value.
The predicted salary is between 48000 - 72000 £ per year.
A leading global financial services provider in Scotland seeks a Lead Machine Learning Engineer to spearhead AI initiatives in Risk Technology. The role involves developing multi-agent systems, leading a diverse team, and collaborating across departments to enhance business value.
Candidates must hold a relevant degree, have extensive ML engineering experience, and be proficient in Python and AWS. This position offers an opportunity to innovate in asset and wealth management risk.
Lead ML Engineer - Agentic AI & Risk Systems in London employer: J.P. Morgan
Contact Detail:
J.P. Morgan Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead ML Engineer - Agentic AI & Risk Systems in London
✨Tip Number 1
Network like a pro! Reach out to folks in the financial services and AI space on LinkedIn. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your ML projects, especially those involving multi-agent systems. This will give you an edge when discussing your experience.
✨Tip Number 3
Prepare for the interview by brushing up on your Python and AWS knowledge. Be ready to discuss how you've used these tools in past projects to drive business value.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets noticed and shows you're serious about joining our team.
We think you need these skills to ace Lead ML Engineer - Agentic AI & Risk Systems in London
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your experience with machine learning and any relevant projects you've worked on. We want to see how you can bring your expertise in Python and AWS to the table!
Tailor Your Application: Don’t just send a generic CV! Customise your application to reflect how your background aligns with our needs in AI initiatives and risk technology. We love seeing candidates who take the time to connect their experience with the role.
Be Clear and Concise: When writing your application, keep it straightforward. We appreciate clarity, so make sure your points are easy to read and get straight to the point about your qualifications and achievements.
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’re considered for this exciting opportunity in asset and wealth management risk!
How to prepare for a job interview at J.P. Morgan
✨Know Your ML Fundamentals
Brush up on your machine learning fundamentals, especially those relevant to risk technology. Be prepared to discuss algorithms, model evaluation, and how you’ve applied these in past projects. This will show your depth of knowledge and passion for the field.
✨Showcase Your Leadership Skills
As a Lead ML Engineer, you'll be expected to lead a diverse team. Prepare examples of how you've successfully managed teams or projects in the past. Highlight your ability to collaborate across departments and drive initiatives that enhance business value.
✨Demonstrate Technical Proficiency
Make sure you can confidently discuss your experience with Python and AWS. Be ready to share specific projects where you utilised these technologies, and consider preparing a small coding challenge or example to demonstrate your skills during the interview.
✨Prepare Questions About Innovation
Since this role involves innovating in asset and wealth management risk, come prepared with insightful questions about the company's current AI initiatives. This shows your interest in their work and helps you understand how you can contribute to their goals.
