Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Develop and deploy bespoke AI solutions for diverse financial services clients.
- Company: Cutting-edge AI company based in England with a supportive team culture.
- Benefits: Flexible working arrangements and opportunities for professional growth.
- Why this job: Make a real impact in the financial sector using innovative AI technologies.
- Qualifications: Strong understanding of machine learning, excellent Python skills, and cloud experience.
- Other info: Collaborate with engineers and lead technical decisions in a dynamic environment.
The predicted salary is between 36000 - 60000 £ per year.
A cutting-edge AI company based in England is seeking a Machine Learning Engineer to develop and deploy bespoke AI solutions for diverse financial services clients. You will build production-grade software, collaborate with engineers, and lead technical decisions to ensure project impact and feasibility.
The ideal candidate will have:
- a strong understanding of the machine learning lifecycle,
- excellent Python skills,
- hands-on experience with cloud platforms and container management tools.
This role allows for flexible working arrangements and emphasizes a supportive team culture.
Production ML Engineer — Financial Services in London employer: Faculty
Contact Detail:
Faculty Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Production ML Engineer — Financial Services in London
✨Tip Number 1
Network like a pro! Reach out to folks in the financial services and AI sectors on LinkedIn. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects. This is your chance to demonstrate your Python prowess and cloud experience in a way that really stands out.
✨Tip Number 3
Prepare for those interviews! Brush up on your knowledge of the machine learning lifecycle and be ready to discuss how you've tackled challenges in past projects. Confidence is key!
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who are proactive and engaged. Plus, it makes it easier for us to connect with you directly.
We think you need these skills to ace Production ML Engineer — Financial Services in London
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your Python expertise and any experience you have with cloud platforms. We want to see how your skills align with the role, so don’t hold back!
Tailor Your Application: Customise your CV and cover letter to reflect the specific requirements of the Production ML Engineer position. We love seeing candidates who take the time to connect their experiences to what we’re looking for.
Be Clear and Concise: When writing your application, keep it straightforward. We appreciate clarity, so make sure your points are easy to read and get straight to the point about your qualifications.
Apply Through Our Website: We encourage you to submit your application through our website. It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at Faculty
✨Know Your ML Lifecycle
Make sure you can confidently discuss the machine learning lifecycle. Brush up on each stage, from data collection to model deployment, and be ready to share examples of how you've navigated these phases in past projects.
✨Show Off Your Python Skills
Prepare to demonstrate your Python expertise. You might be asked to solve a coding problem or explain your approach to a specific task. Practise common algorithms and libraries relevant to machine learning, so you can showcase your skills effectively.
✨Familiarise Yourself with Cloud Platforms
Since this role involves cloud platforms, make sure you're well-versed in at least one major provider like AWS, Azure, or Google Cloud. Be ready to discuss how you've used these tools in previous projects, especially in relation to deploying machine learning models.
✨Emphasise Team Collaboration
This position values a supportive team culture, so highlight your experience working collaboratively. Prepare examples of how you've contributed to team projects, resolved conflicts, or led technical discussions to ensure everyone is on the same page.