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- Tasks: Build innovative systems using generative AI to enhance financial data.
- Company: Leading financial data provider in Greater London with a focus on technology.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Why this job: Join a fast-paced environment and make a real impact in the finance sector.
- Qualifications: 3+ years in software engineering, strong skills in AI/ML, Python, and cloud architecture.
- Other info: Collaborative team culture with exciting projects and career advancement potential.
The predicted salary is between 43200 - 72000 £ per year.
A leading financial data provider in Greater London is looking for a skilled Software Engineer to work with generative AI technologies. The role involves building systems to enrich financial data, monitoring performance, and collaborating with various teams.
Candidates should have over 3 years of software engineering experience, particularly in AI/ML solutions, with a solid grasp of cloud architecture and Python development. This role offers a chance to make impactful contributions in a fast-paced environment.
GenAI ML Engineer - Python, Docker, API (RAG & Data) in London employer: FactSet
Contact Detail:
FactSet Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land GenAI ML Engineer - Python, Docker, API (RAG & Data) in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. 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 projects, especially those involving Python, Docker, and AI/ML. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and understanding the latest trends in generative AI. Practice common interview questions and be ready to discuss your past experiences in detail.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might just be the perfect fit for you. Plus, it’s a great way to ensure your application gets seen by the right people.
We think you need these skills to ace GenAI ML Engineer - Python, Docker, API (RAG & Data) in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python, Docker, and AI/ML solutions. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Tell us why you’re excited about working with generative AI technologies and how you can contribute to enriching financial data. Keep it engaging and personal.
Showcase Your Projects: If you've worked on any cool projects related to cloud architecture or financial data, make sure to mention them! We love seeing practical examples of your work that demonstrate your skills and creativity.
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 don’t miss out on any important updates from our team!
How to prepare for a job interview at FactSet
✨Know Your Tech Inside Out
Make sure you brush up on your Python skills and any relevant frameworks. Be ready to discuss your experience with Docker and APIs, as well as how you've applied generative AI technologies in past projects.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of how you've tackled challenges in software engineering. Think about times when you improved system performance or collaborated with teams to deliver AI/ML solutions.
✨Understand the Financial Sector
Familiarise yourself with the financial data landscape. Knowing how generative AI can enhance financial data will show that you're not just a tech whiz but also understand the industry context.
✨Ask Insightful Questions
Prepare thoughtful questions about the company's approach to AI/ML and their team dynamics. This shows your genuine interest in the role and helps you gauge if it's the right fit for you.