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- Tasks: Deploy and optimise AI/ML models for real-world applications in finance.
- Company: Join a leading financial services organisation with a focus on innovation.
- Benefits: Competitive pay, flexible working, and opportunities for professional growth.
- Why this job: Make a tangible impact in AI while developing your skills in a dynamic environment.
- Qualifications: Strong Python skills and experience with ML frameworks and MLOps tools.
- Other info: Enjoy autonomy and exposure to senior stakeholders in a hands-on role.
The predicted salary is between 36000 - 60000 £ per year.
The Siena Partnership are working with a leading financial services organisation seeking a Senior Full Stack AI/ML Engineer for an initial 6-month contract. This role focuses on taking AI models built by a third-party provider and turning them into robust, production-grade systems, while helping establish a long-term internal AI/ML engineering capability.
What you’ll do:
- Deploy and operationalise AI/ML models into live production environments
- Build observability, monitoring, and continuous evaluation to manage model performance and drift
- Design and implement CI/CD pipelines for scalable, reproducible model delivery
- Optimise performance, reliability, and efficiency of existing AI solutions
- Set up tooling for model serving, versioning, and lifecycle management
- Lead documentation, knowledge transfer, and mentoring to upskill internal teams
Technical requirements:
- Strong Python and ML frameworks (PyTorch, TensorFlow)
- MLOps tooling (MLflow, Kubeflow or similar)
- Docker, Kubernetes, CI/CD pipelines
- Cloud platforms (AWS, Azure or GCP); Terraform experience preferred
- Financial services experience highly desirable
A hands-on role with real impact, autonomy, and senior stakeholder exposure.
Senior AI Engineer employer: Siena Partnership
Contact Detail:
Siena Partnership Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior AI Engineer
✨Tip Number 1
Network like a pro! Reach out to your connections in the financial services sector and let them know you're on the lookout for a Senior AI Engineer role. A personal recommendation can make all the difference.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI/ML projects, especially those involving Python and MLOps tooling. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Be ready to discuss how you've deployed AI models in production environments and optimised their performance.
✨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 get noticed by hiring managers directly.
We think you need these skills to ace Senior AI Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Senior AI Engineer role. Highlight your experience with Python, ML frameworks, and any relevant financial services background. We want to see how your skills match what we're looking for!
Showcase Your Projects: Include specific projects where you've deployed AI/ML models or worked with CI/CD pipelines. We love seeing real examples of your work, so don’t hold back on the details that show off your expertise!
Craft a Compelling Cover Letter: Your cover letter should tell us why you're the perfect fit for this role. Share your passion for AI/ML and how you can contribute to building robust systems. We appreciate a personal touch that reflects your enthusiasm!
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 makes the process smoother for everyone involved!
How to prepare for a job interview at Siena Partnership
✨Know Your AI Inside Out
Make sure you’re well-versed in the AI models and frameworks mentioned in the job description, like PyTorch and TensorFlow. Be ready to discuss your past experiences with these technologies and how you've deployed them in production environments.
✨Showcase Your MLOps Skills
Prepare to talk about your experience with MLOps tooling such as MLflow or Kubeflow. Highlight specific projects where you’ve implemented CI/CD pipelines and how you’ve optimised model performance and reliability.
✨Demonstrate Financial Services Knowledge
If you have experience in financial services, make sure to bring it up! Discuss how your background can help the company establish a robust internal AI/ML capability and how you understand the unique challenges in this sector.
✨Be Ready for Technical Challenges
Expect some technical questions or even a practical test during the interview. Brush up on Docker, Kubernetes, and cloud platforms like AWS or Azure. Being able to solve problems on the spot will show your hands-on expertise.
