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- Tasks: Transform AI models into robust systems and optimise their performance in production.
- Company: Join a leading financial services organisation with a focus on innovation.
- Benefits: Flexible remote work, competitive pay, and potential for contract extension or permanent role.
- Why this job: Be at the forefront of AI/ML engineering and make a real impact in finance.
- Qualifications: Strong Python skills and experience with ML frameworks like PyTorch or TensorFlow.
- Other info: Opportunity to build internal AI capabilities in a dynamic environment.
The predicted salary is between 43200 - 72000 £ 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 (with the potential to extend or go perm).
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.
- Deploy and operationalise AI/ML models into live production environments
- Build observability, monitoring, and continuous evaluation to manage model performance and drift
- Optimise performance, reliability, and efficiency of existing AI solutions
Strong Python and ML frameworks (PyTorch, TensorFlow); Cloud platforms (AWS, Azure or GCP); Financial services experience highly desirable.
AI Engineer (Remote) in London employer: Siena Partnership
Contact Detail:
Siena Partnership Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Engineer (Remote) in London
✨Tip Number 1
Network like a pro! Reach out to folks in the financial services sector or AI/ML communities. You never know who might have the inside scoop on job openings or can refer you directly to hiring managers.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI/ML projects, especially those using Python and frameworks like PyTorch or TensorFlow. This will give potential employers a taste of what you can do.
✨Tip Number 3
Prepare for technical interviews by brushing up on your cloud platform knowledge (AWS, Azure, GCP). Be ready to discuss how you've deployed AI models in production environments and tackled performance issues.
✨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 our team.
We think you need these skills to ace AI Engineer (Remote) in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with AI/ML models and the specific frameworks mentioned in the job description. We want to see how your skills align with what we're looking for, so don’t be shy about showcasing your Python prowess and cloud platform experience!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about AI engineering and how your background makes you a perfect fit for this role. We love seeing enthusiasm and a clear understanding of the financial services sector.
Showcase Relevant Projects: If you've worked on any projects that involved deploying AI/ML models or optimising performance, make sure to mention them. We’re keen to see real-world examples of your work, especially if they relate to production-grade systems!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to keep track of your application and ensure it gets the attention it deserves. Plus, it shows you’re serious about joining our team!
How to prepare for a job interview at Siena Partnership
✨Know Your AI Stuff
Make sure you brush up on your knowledge of AI and ML frameworks, especially Python, PyTorch, and TensorFlow. Be ready to discuss how you've used these technologies in past projects, as well as any challenges you've faced and how you overcame them.
✨Showcase Your Deployment Skills
Since the role involves deploying AI models into production, be prepared to talk about your experience with cloud platforms like AWS, Azure, or GCP. Share specific examples of how you've operationalised models and ensured their performance in live environments.
✨Demonstrate Problem-Solving Abilities
Highlight your ability to optimise existing AI solutions. Think of instances where you've improved performance, reliability, or efficiency, and be ready to explain your thought process and the impact of your work.
✨Understand the Financial Services Landscape
If you have experience in financial services, make sure to mention it! If not, do some research on how AI is being used in this sector. Showing that you understand the industry will set you apart and demonstrate your commitment to the role.
