At a Glance
- Tasks: Design AI models and integrate features to support investment professionals.
- Company: Leading asset management firm in Greater London with a diverse workplace.
- Benefits: Competitive benefits, training opportunities, and performance-based incentives.
- Why this job: Join a dynamic team and shape the future of investment with AI.
- Qualifications: Master’s or Ph.D. in AI, strong Python skills, and experience with AI frameworks.
- Other info: Exciting opportunity for growth in the financial services sector.
The predicted salary is between 43200 - 72000 £ per year.
A leading asset management firm in Greater London is seeking a talented AI/ML Engineer to support investment professionals by designing models and integrating AI features into products.
Candidates should hold a Master’s or Ph.D. in Artificial Intelligence and have strong Python skills. Experience with AI frameworks is critical, and financial services background is preferred.
The firm promotes a diverse workplace and offers competitive benefits, including training opportunities and performance-based incentives.
AI Engineer - Investment AI, ML & Automation in London employer: Capstone
Contact Detail:
Capstone Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Engineer - Investment AI, ML & Automation in London
✨Tip Number 1
Network like a pro! Reach out to professionals in the AI and finance sectors on LinkedIn. Join relevant groups and engage in discussions to get your name out there and learn about hidden job opportunities.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI projects, especially those related to investment or financial services. This will give you an edge and demonstrate your practical experience to potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice common AI/ML interview questions and be ready to discuss your past projects in detail. We want you to shine!
✨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 and take the initiative to connect with us directly.
We think you need these skills to ace AI Engineer - Investment AI, ML & Automation in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your relevant experience in AI and ML, especially any projects or roles that align with investment strategies. We want to see how your skills can directly contribute to our team!
Showcase Your Python Skills: Since strong Python skills are a must, include specific examples of how you've used Python in your previous work. We love seeing practical applications of your coding prowess!
Highlight Your AI Framework Experience: Mention any AI frameworks you’ve worked with, as this is critical for the role. We’re keen to know how you’ve integrated these into your projects, so don’t hold back!
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It’s the best way for us to receive your application and get to know you better!
How to prepare for a job interview at Capstone
✨Know Your AI Inside Out
Make sure you brush up on your knowledge of AI and ML concepts, especially those relevant to investment. Be prepared to discuss specific models you've designed or worked with, and how they can be applied in financial services.
✨Show Off Your Python Skills
Since strong Python skills are a must, practice coding problems that relate to AI and data manipulation. You might be asked to solve a problem on the spot, so being comfortable with Python libraries like TensorFlow or PyTorch will give you an edge.
✨Understand the Financial Landscape
Having a background in financial services is preferred, so do your homework on the firm’s investment strategies and market trends. This will help you connect your technical skills to real-world applications during the interview.
✨Embrace Diversity and Inclusion
The firm values a diverse workplace, so be ready to discuss how your unique experiences can contribute to their culture. Share examples of how you've worked in diverse teams or how you approach inclusivity in your projects.