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- Tasks: Design scalable backend systems and integrate AI features into fintech products.
- Company: Fast-growing fintech company in London with a focus on innovation.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Other info: Dynamic and fast-paced environment with excellent career advancement potential.
- Why this job: Join a team redefining financial data usage with cutting-edge AI technology.
- Qualifications: Strong Python skills and hands-on experience with Large Language Models.
The predicted salary is between 60000 - 80000 £ per year.
Station, a fast-growing fintech company in London, is seeking a Python Engineer to leverage AI and Large Language Models (LLMs). In this impactful role, you will design scalable backend systems, integrate LLM features into products, and collaborate closely with product and engineering teams.
Ideal candidates will have:
- Strong Python experience
- Hands-on knowledge of LLMs
- The ability to thrive in a fast-paced, innovative environment
Join Station to help build products that redefine financial data usage.
Python Engineer - AI & LLMs for Fintech Scale employer: Station
Contact Detail:
Station Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Python Engineer - AI & LLMs for Fintech Scale
✨Tip Number 1
Network like a pro! Reach out to folks in the fintech space, especially those working with AI and LLMs. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a GitHub repo or a personal project showcasing your Python prowess and any LLM integrations you've done. This gives us something tangible to look at beyond your application.
✨Tip Number 3
Prepare for the interview by brushing up on your problem-solving skills. We love candidates who can think on their feet, so practice coding challenges and be ready to discuss your thought process.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team at Station.
We think you need these skills to ace Python Engineer - AI & LLMs for Fintech Scale
Some tips for your application 🫡
Show Off Your Python Skills: Make sure to highlight your Python experience in your application. We want to see how you've used Python in real-world projects, especially if you've worked with AI or LLMs before. Don't hold back on the details!
Tailor Your Application: Take a moment to customise your application for this role. Mention specific projects or experiences that relate to designing scalable backend systems or integrating LLM features. We love seeing how you connect your background to what we do at Station.
Be Yourself: Let your personality shine through in your written application. We’re looking for innovative thinkers who can thrive in a fast-paced environment, so don’t be afraid to show us what makes you unique and how you approach problem-solving.
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 the role. Plus, it gives you a chance to explore more about what we do at Station!
How to prepare for a job interview at Station
✨Know Your Python Inside Out
Make sure you brush up on your Python skills before the interview. Be ready to discuss your experience with Python, especially in relation to backend systems. Practise coding challenges that focus on Python to demonstrate your proficiency.
✨Familiarise Yourself with LLMs
Since the role involves working with Large Language Models, take some time to understand how they work and their applications in fintech. Be prepared to discuss any projects you've worked on that involved LLMs, showcasing your hands-on knowledge.
✨Showcase Your Problem-Solving Skills
In a fast-paced environment like Station, problem-solving is key. Think of examples from your past experiences where you tackled complex issues or optimised processes. Use the STAR method (Situation, Task, Action, Result) to structure your answers.
✨Collaborate and Communicate
This role requires close collaboration with product and engineering teams. Be ready to talk about your teamwork experiences and how you communicate technical concepts to non-technical stakeholders. Highlight any successful collaborations that led to impactful results.