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- Tasks: Build and deploy cutting-edge machine learning systems in the FinTech sector.
- Company: Join innovative Series A-C FinTech AI companies scaling their engineering teams.
- Benefits: Competitive salary, equity options, and flexible remote work arrangements.
- Other info: Exciting opportunities for career growth in a dynamic and regulated environment.
- Why this job: Make a real impact in financial services with advanced AI technologies.
- Qualifications: 5+ years of experience in production ML systems and strong knowledge of modern AI tools.
The predicted salary is between 90000 - 120000 £ per year.
I am working with several Series A-C FinTech AI companies hiring Senior ML Engineers and Senior AI Engineers across the UK right now. Not LLM wrappers – real production systems. Risk modelling, fraud detection, agentic compliance, transaction intelligence, retrieval‑augmented generation pipelines running over financial data in regulated environments.
Companies that have closed funding in the last twelve months and are scaling the engineering team that has to make AI actually work inside Financial Services.
Technical bar (broadly):
- 5+ years building and shipping Machine Learning systems in production
- Strong on the modern AI stack – PyTorch, HuggingFace, LangChain, LangGraph, vector databases and RAG pipelines
- Comfortable owning a model end‑to‑end: data, training, evaluation, deployment and monitoring (MLOps / LLMOps)
Bonus ball: exposure to regulated environments – FinTech, banking, payments, insurance
Packages £90K-£120K depending on experience, plus meaningful equity. London‑based hybrid or fully remote for the right background (UK only though).
Senior Machine Learning Engineer employer: HorizonAI Talent
Contact Detail:
HorizonAI Talent Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Machine Learning Engineer
✨Tip Number 1
Network like a pro! Reach out to your connections in the FinTech space and let them know you're on the lookout for Senior ML Engineer roles. A personal recommendation can go a long way in getting your foot in the door.
✨Tip Number 2
Showcase your skills! Create a portfolio of your past projects, especially those involving risk modelling or fraud detection. This will help you stand out and demonstrate your hands-on experience with the modern AI stack.
✨Tip Number 3
Prepare for technical interviews by brushing up on your MLOps knowledge. Be ready to discuss how you've owned models end-to-end, from data handling to deployment. Companies want to see that you can make AI work in regulated environments.
✨Tip Number 4
Don't forget to apply through our website! We have loads of exciting opportunities with companies scaling their engineering teams. It's a great way to get noticed and land that dream job in the FinTech sector.
We think you need these skills to ace Senior Machine Learning Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the role of Senior Machine Learning Engineer. Highlight your experience with production systems, especially in FinTech, and showcase your skills with the modern AI stack like PyTorch and HuggingFace.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about AI in financial services and how your background makes you a perfect fit for the role. Be specific about your achievements and how they relate to the job.
Showcase Your Projects: If you've worked on relevant projects, make sure to include them in your application. Whether it's risk modelling or fraud detection, real-world examples will help us see your expertise in action and how you can contribute to our team.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at HorizonAI Talent
✨Know Your Tech Stack
Make sure you’re well-versed in the modern AI stack mentioned in the job description. Brush up on your skills with PyTorch, HuggingFace, and LangChain. Be ready to discuss how you've used these tools in real production systems.
✨Showcase Your End-to-End Experience
Prepare to talk about your experience owning machine learning models from data collection to deployment. Highlight specific projects where you’ve managed the entire lifecycle, including training, evaluation, and monitoring.
✨Understand the FinTech Landscape
Familiarise yourself with the challenges and regulations in the FinTech sector. Be prepared to discuss how your work can contribute to risk modelling, fraud detection, and compliance in a regulated environment.
✨Ask Insightful Questions
Come equipped with thoughtful questions about the company’s current projects and future goals. This shows your genuine interest and helps you gauge if the company aligns with your career aspirations.