Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Develop and implement AI/ML models to tackle real-world challenges.
- Company: Leading tech firm focused on innovative AI solutions.
- Benefits: Attractive salary, flexible working hours, and growth opportunities.
- Other info: Fast-paced environment with endless learning and career advancement.
- Why this job: Join a dynamic team and shape the future of technology with AI.
- Qualifications: Experience in Python and data science; passion for AI/ML.
The predicted salary is between 50000 - 65000 £ per year.
As an Applied AIML Engineer, you will leverage your advanced technical capabilities to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. You will work as part of an agile team to deploy best‑in‑class AI/ML solutions that solve complex operational challenges.
Job Responsibilities:
- Co‑Develop and implement LLM‑based, machine learning models and algorithms to solve complex operational challenges.
- Design and deploy generative AI applications to automate and optimize business processes.
- Collaborate with stakeholders.
Applied AIML Associate - Python & Data Science Engineering employer: J.P. Morgan
Contact Detail:
J.P. Morgan Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Applied AIML Associate - Python & Data Science Engineering
✨Tip Number 1
Network like a pro! Reach out to professionals in the AIML field on LinkedIn or at industry events. A friendly chat can open doors and give you insights that might just land you that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving LLM-based models or generative AI applications. This will give potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice common AIML interview questions and be ready to discuss how you've tackled complex challenges in the past.
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who are genuinely interested in joining our team. Plus, it’s a great way to ensure your application gets the attention it deserves.
We think you need these skills to ace Applied AIML Associate - Python & Data Science Engineering
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your technical capabilities in Python and data science. We want to see how you can leverage these skills to build and deliver top-notch AI/ML solutions.
Tailor Your Application: Don’t just send a generic application! Customise your CV and cover letter to reflect the job description. We love seeing how your experience aligns with our needs, especially in deploying generative AI applications.
Be Clear and Concise: When writing your application, keep it clear and to the point. We appreciate straightforward communication that showcases your problem-solving abilities without unnecessary fluff.
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’s super easy!
How to prepare for a job interview at J.P. Morgan
✨Know Your Tech Inside Out
Make sure you’re well-versed in Python and data science concepts. Brush up on your knowledge of machine learning models, especially LLMs, as you’ll likely be asked to discuss how you’ve implemented these in past projects.
✨Showcase Your Problem-Solving Skills
Prepare examples of complex operational challenges you've tackled using AI/ML solutions. Be ready to explain your thought process and the impact of your solutions, as this will demonstrate your ability to think critically and innovate.
✨Understand Agile Methodologies
Since you’ll be working in an agile team, it’s crucial to understand agile principles. Familiarise yourself with how agile teams operate and be prepared to discuss your experience working in such environments.
✨Engage with Stakeholders
Collaboration is key in this role. Think about times when you’ve worked with stakeholders to gather requirements or feedback. Be ready to share how you effectively communicated technical concepts to non-technical audiences.