At a Glance
- Tasks: Develop AI-powered products and optimise business processes using cutting-edge technologies.
- Company: Join JPMorganChase, a global leader in financial services with a focus on innovation.
- Benefits: Competitive salary, diverse work culture, and opportunities for professional growth.
- Other info: Diverse and inclusive workplace with excellent career advancement opportunities.
- Why this job: Be at the forefront of AI innovation and make a real impact in the industry.
- Qualifications: Advanced degree in STEM and experience in AI/ML model development.
The predicted salary is between 70000 - 90000 £ per year.
As a Software Engineer II - Applied AI in the AI/ML for Engineering team at JPMorganChase, you'll be at the forefront of AI innovation, combining cutting-edge techniques with unique data assets to optimise business decisions and automate processes. This role offers a unique blend of artificial intelligence and software engineering, allowing you to advance engineering processes and build impactful products.
In this role, you will leverage the latest research in Large Language Models, Natural Language Processing and statistical machine learning to build AI-powered products that automate processes and enhance decision-making. You will collaborate with engineering and testing teams to design scalable Machine Learning services and communicate AI capabilities to diverse audiences.
- Development of advanced machine learning models to address complex operational challenges.
- Architect and oversee the deployment of generative AI applications and agents to automate and enhance business processes.
- Analyze large datasets to extract actionable insights and support data-driven decision-making at a strategic level.
- Ensure the scalability, reliability, and security of AI/ML solutions in a production environment, with a focus on long-term sustainability.
- Stay informed about the latest advancements in AI/ML technologies and drive their integration into our operations.
Qualifications:
- Advanced degree in a STEM field (Degree in Computer Science or Software Engineering), with experience in AI/ML.
- Proven track record of AI/ML model development and deployment of AI/ML applications in a production environment, with expertise in deploying models on AWS platforms.
- Deep familiarity with MLOps practices, covering the full cycle from design, experimentation, deployment, to monitoring and maintenance of machine learning models.
- Expertise in machine learning frameworks such as TensorFlow, PyTorch, PyTorch Lightning, or Scikit-learn.
- Proficiency in Python with a strong emphasis on code quality and reliability through comprehensive testing.
- Extensive experience with generative AI models, mainly as cloud service APIs.
- Experience with integrating user feedback to establish self-improving AI applications.
- Solid understanding of data preprocessing, feature engineering, and model evaluation techniques.
- Familiarity with cloud platforms (AWS).
- Experience in software engineering practices.
- Experience in developing AI solutions using agentic frameworks.
- Experience with prompt optimisation to enhance the performance and effectiveness of prompt engineering.
- Demonstrated ability to design and implement AI application architecture.
- Significant experience in bringing AI applications to production with a focus on strategic impact and innovation.
We strive to build trusted, long-term partnerships to help our clients achieve their business objectives. We recognise that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, colour, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs.
StudySmarter Expert Advice🤫
We think this is how you could land AI Software Engineer in London
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at J.P. Morgan or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to J.P. Morgan.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like J.P. Morgan.
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like J.P. Morgan that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace AI Software Engineer in London
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at J.P. Morgan.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at J.P. Morgan and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at J.P. Morgan
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If J.P. Morgan uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.