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- Tasks: Develop and deploy cutting-edge AI systems using Python on innovative projects.
- Company: A leading AI-focused startup in the heart of London.
- Benefits: Competitive and flexible compensation for top-tier talent.
- Why this job: Join a dynamic team and work on impactful greenfield projects in AI.
- Qualifications: Strong Python skills, MLOps experience, and a passion for finance.
- Other info: Engage with investors and thrive in a fast-paced environment.
The predicted salary is between 36000 - 60000 £ per year.
A leading AI-focused startup in London is seeking an experienced AI Engineer to work on innovative greenfield projects. The role emphasizes Python development, performance, and the deployment of AI systems.
Candidates should possess strong Python skills, ideally with a background in Data Science or Software Engineering, and experience in MLOps. The position is front office facing, requiring interaction with investors, and an interest in finance is highly valued.
Compensation is competitive and flexible for top-tier talent.
Production AI Engineer: Python, MLOps & Front-Office employer: DW Search
Contact Detail:
DW Search Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Production AI Engineer: Python, MLOps & Front-Office
✨Tip Number 1
Network like a pro! Reach out to people in the AI and finance 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 Python projects, especially those related to MLOps. This will give you an edge when discussing your experience.
✨Tip Number 3
Prepare for the interview by brushing up on your knowledge of AI systems and their deployment. Be ready to discuss how you can contribute to innovative greenfield projects.
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who are proactive and engaged with our platform. It shows you're serious about landing that role.
We think you need these skills to ace Production AI Engineer: Python, MLOps & Front-Office
Some tips for your application 🫡
Show Off Your Python Skills: Make sure to highlight your Python expertise in your application. We want to see how you've used Python in past projects, especially in AI and MLOps. Don't hold back on showcasing any innovative solutions you've developed!
Connect Your Experience to Finance: Since this role is front office facing, it’s a good idea to mention any experience you have in finance or working with investors. We love candidates who can bridge the gap between tech and finance, so let us know how you fit into that picture!
Be Clear and Concise: When writing your application, keep it clear and to the point. We appreciate well-structured applications that get straight to the heart of your experience and skills. Remember, less is often more!
Apply Through Our Website: We encourage you to apply directly through our website. It makes it easier for us to track your application and ensures you don’t miss out on any important updates. Plus, we love seeing applications come through our own platform!
How to prepare for a job interview at DW Search
✨Master Your Python Skills
Make sure you brush up on your Python skills before the interview. Be ready to discuss your previous projects and how you've used Python in real-world applications, especially in AI and MLOps. Practising coding challenges can also help you demonstrate your technical prowess.
✨Showcase Your MLOps Knowledge
Since this role emphasises MLOps, be prepared to talk about your experience with deploying machine learning models. Discuss any tools or frameworks you've used, and be ready to explain how you ensure performance and scalability in your projects.
✨Understand the Finance Aspect
Given that the position is front office facing, having a basic understanding of finance will set you apart. Familiarise yourself with key financial concepts and be ready to discuss how AI can impact the finance sector. This shows your interest and helps you connect with potential investors.
✨Prepare for Behavioural Questions
Don’t forget to prepare for behavioural questions! Think of examples from your past experiences that highlight your problem-solving skills, teamwork, and adaptability. Use the STAR method (Situation, Task, Action, Result) to structure your answers effectively.
