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- Tasks: Build and deploy cutting-edge AI systems using Python in a dynamic startup environment.
- Company: Exciting AI startup backed by a major investment firm in London.
- Benefits: Competitive salary up to £200k, flexible work options, and growth opportunities.
- Why this job: Join top-tier AI engineers and make a real impact in the finance sector.
- Qualifications: Strong Python skills and experience in MLOps or software engineering required.
- Other info: Collaborative culture with a focus on innovation and business value.
The predicted salary is between 72000 - 120000 £ per year.
New AI startup within a major investment firm in London is seeking an experienced AI Engineer with a strong software engineering foundation and a track record of building AI systems that run in production. This role is front office facing, and we are looking for exceptional technical talent who care about driving business value and enjoy working closely with users.
You can expect to work on greenfield AI projects using Python as a first-class language, with a strong focus on fundamentals, performance, and correctness. The work spans production LLM and ML systems, data pipelines, model deployment, monitoring, and iteration. You will be building and owning systems end to end, including infrastructure and MLOps, across Azure and AWS environments.
In terms of background, we are open to Data Scientist or Software Engineer backgrounds, but strong Python is mandatory. We are looking for engineers who really understand Python, including internals and core language behaviour, and who are comfortable designing, deploying, and maintaining AI systems in production. You will be tested on Python fundamentals early in the process. Experience with MLOps, model lifecycle management, and operating AI systems at scale is essential. Financial services experience is a plus, as you will be working closely with investors, but a genuine interest in finance is just as important.
For top-tier AI Engineers, this is a rare opportunity to work alongside some of the most advanced AI practitioners in London, building systems that are used, trusted, and commercially impactful.
Responsibilities:- Work on greenfield AI projects with a focus on Python development, performance, and correctness.
- Design, deploy, monitor, and iterate production AI systems including LLMs and ML pipelines.
- Own systems end to end, including infrastructure and MLOps across Azure and AWS.
- Collaborate closely with users and front office teams to drive business value.
- Strong Python expertise, including understanding Python internals and core language behaviour.
- Background in Data Science or Software Engineering; either is acceptable with strong Python as mandatory.
- Experience with MLOps, model lifecycle management, and operating AI systems at scale.
- Willingness to work in a front office facing role and interact with investors; interest in finance is important.
AI Engineer in London employer: DW Search
Contact Detail:
DW Search Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land AI Engineer in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the AI and finance sectors. Attend meetups, webinars, or even casual coffee chats. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI projects, especially those using Python. Share your work on platforms like GitHub or even your own website. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for technical interviews by brushing up on Python fundamentals. Practice coding challenges and be ready to discuss your past projects in detail. We want to see how you think and solve problems, so be confident!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team. Don’t miss out on this opportunity!
We think you need these skills to ace AI Engineer in London
Some tips for your application 🫡
Show Off Your Python Skills: Make sure to highlight your strong Python expertise in your application. We want to see your understanding of Python internals and core language behaviour, so don’t hold back on showcasing any relevant projects or experiences!
Tailor Your Application: Take the time to tailor your application to the role. Mention your experience with MLOps, model lifecycle management, and any AI systems you've worked on. We love seeing how your background aligns with our needs!
Express Your Interest in Finance: Since this role involves working closely with investors, it’s important to express your genuine interest in finance. Share any relevant experiences or insights that demonstrate your passion for the financial sector.
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’re considered for this exciting opportunity with our team!
How to prepare for a job interview at DW Search
✨Master Your Python Fundamentals
Since strong Python expertise is mandatory for this role, make sure you brush up on your Python fundamentals. Be prepared to answer questions about the internals and core behaviour of the language. Practising coding challenges or reviewing key concepts can really help you shine.
✨Showcase Your AI Experience
Highlight any previous experience you've had with building AI systems, especially in production environments. Be ready to discuss specific projects where you designed, deployed, or monitored AI systems. This will demonstrate your hands-on experience and understanding of MLOps.
✨Understand the Business Value
This role is front office facing, so it's crucial to show that you understand how AI can drive business value. Research the company’s focus areas and think about how your skills can contribute to their goals. Being able to articulate this during the interview will set you apart.
✨Prepare for Technical Questions
Expect technical questions that test your knowledge of model lifecycle management and operating AI systems at scale. Review common scenarios and be ready to discuss how you would approach challenges in these areas. Confidence in your technical abilities will go a long way!
