At a Glance
- Tasks: Lead the development of cutting-edge LLM applications in a collaborative environment.
- Company: Join JP Morgan Asset Management, a leader in innovative financial technology.
- Benefits: Competitive salary, diverse culture, and opportunities for professional growth.
- Other info: Be part of a dynamic team focused on diversity, equity, and inclusion.
- Why this job: Make an impact by building scalable ML products that shape the future of asset management.
- Qualifications: Degree in computer science, advanced Python skills, and experience with cloud technologies.
The predicted salary is between 70000 - 90000 £ per year.
Opportunity JP Morgan Asset Management is expanding LLM use cases across AM business areas. We are seeking a software engineer with expertise in python and prior experience in utilizing LLMs. As an LLM Engineering Lead within Asset Management you will be collaborating closely with various teams to prototype, build, test and deploy a large scale federated LLM platform. You will work with an agile team that will build and deliver trusted market‑leading technology products in a secure, stable, and scalable way. You will partner with our Global Data Science teams to design, develop, deploy and operate machine learning driven applications and data pipelines.
Responsibilities
- Hands‑on involvement in building and operating highly sophisticated LLM driven applications.
- Partner directly with other technology teams on LLM projects to advise and assist as needed.
- Collaborate with Data Science, Cybersecurity to deliver state‑of‑the‑art ML products.
- Manage and support a team of ML and MLOps engineers.
- Collaborate with DevOps engineers to plan and deploy data storage and processing systems.
- Execute creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches.
- Develop secure high‑quality production code, and review and debug code written by others.
- Contribute to a culture of diversity, equity, inclusion, and respect.
Required Qualifications, Capabilities, and Skills
- Formal training or certification on software engineering concepts and advanced applied experience.
- Degree‑level education in computer science or related discipline.
- Advanced Python programming skills.
- Proven experience building and operating scalable ML‑driven products.
- AWS and/or Azure Certifications (Architect, Big Data, AI/ML).
- Hands‑on experience in Azure and AWS.
- Proficiency with cloud technologies like Kubernetes, Airflow.
- Experience working in a highly regulated environment.
- Proven ability to iterate quickly.
- Proficiency in all aspects of the Software Development Life Cycle.
- Terraform and IaaC experience.
- Experience designing and delivering large‑scale cloud‑native architectures.
- Experience with microservices performance tuning, performance optimization, real‑time applications.
Preferred Qualifications, Capabilities, and Skills
- Experience with financial data and data science.
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, color, 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.
Machine Learning Engineering / Applied AI ML Lead - Asset Management Research Technology in London employer: JPMorgan Chase
JP Morgan Asset Management is an exceptional employer, offering a dynamic work environment where innovation thrives. As part of our agile team, you'll have the opportunity to collaborate with top-tier professionals in the field, driving cutting-edge machine learning applications while benefiting from a culture that prioritises diversity, equity, and inclusion. With access to extensive employee growth opportunities and a commitment to professional development, you will be well-equipped to advance your career in a supportive and forward-thinking atmosphere.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineering / Applied AI ML Lead - Asset Management Research Technology 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 JPMorgan Chase 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
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✨Tap into Online Developer Communities
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We think you need these skills to ace Machine Learning Engineering / Applied AI ML Lead - Asset Management Research Technology 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 JPMorgan Chase.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at JPMorgan Chase 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 JPMorgan Chase
✨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 JPMorgan Chase 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.
