At a Glance
- Tasks: Join us to build and maintain cutting-edge ML solutions in a dynamic team environment.
- Company: J.P. Morgan is a global leader in financial services, committed to innovation and diversity.
- Benefits: Enjoy flexible work options, competitive pay, and opportunities for professional growth.
- Other info: We value diversity and inclusion, offering a supportive workplace for all.
- Why this job: Be part of a transformative team shaping the future of banking with AI technology.
- Qualifications: Strong Python skills and experience with LLMs in production are essential.
The predicted salary is between 36000 - 60000 £ per year.
At Chase UK, we\'re redefining digital banking by harnessing cutting-edge technology to deliver seamless, intuitive experiences for our customers. Our engineering team operates with a start-up mindset, empowered to shape the future of banking through scalable, reliable, and innovative solutions. If you\'re passionate about operationalizing advanced machine learning-including large language models (LLMs) and generative AI-this is the place for you.
As a Mid-Level ML Engineer within the International Consumer Bank at JPMorgan Chase, you\'ll work alongside ML scientists, Data Engineers and software engineers to build, deploy, and maintain sophisticated machine learning solutions in production. You\'ll play a hands-on role in implementing ML pipelines, deploying models (including LLMs), and developing the supporting infrastructure that keeps our AI-driven products robust and scalable.
Job Responsibilities:
- Build, automate, and maintain ML pipelines for deploying advanced models, including large language models (LLMs), at scale.
- Collaborate with data engineers, scientists and product owners to operationalize workflows for reliable, seamless model deployment and monitoring.
- Implement monitoring, logging, and alerting for AI services, ensuring performance, security, and compliance in production environments.
- Write clean, maintainable, and efficient Python code for ML tooling, orchestration, and infrastructure.
- Develop and maintain infrastructure as code (IaC) using tools such as Terraform or CloudFormation.
- Work with containerization and orchestration technologies (e.g., Docker, Kubernetes) to support scalable and repeatable deployments of AI services.
- Apply robust software engineering best practices-version control, CI/CD, code reviews, testing, and automation-to all aspects of the ML lifecycle.
- Troubleshoot and optimize ML workflows, from initial development through deployment and production support.
- Engage in cross-functional squads, participating in technical discussions, design reviews, and continuous improvement initiatives.
- Contribute to team growth by sharing knowledge and mentoring junior engineers as needed.
- Strong software engineering background, with deep proficiency in Python (and optionally, Go or Java).
- Demonstrated experience deploying and maintaining LLMs (e.g., GPT\'s, Llama) in production environments.
- Familiarity with frameworks and tooling for LLMs and generative AI (e.g., Transformers, LangChain, Haystack, OpenAI, Vertex AI).
- Experience operationalizing ML solutions in cloud-native environments (AWS, GCP, Azure).
- Proficiency with containerization and orchestration (Docker, Kubernetes or similar) for scalable model deployment.
- Practical experience with infrastructure-as-code (Terraform, CloudFormation, etc.).
- Understanding of concurrency, distributed systems, and scalable API development for ML-powered applications.
- Experience with version control (Git) and CI/CD pipelines.
- Strong problem-solving skills, attention to detail, and a collaborative, growth-focused mindset.
- Experience working in agile, product-driven engineering teams.
- Exposure to Retrieval-Augmented Generation (RAG) pipelines, vector databases (e.g., Pinecone, Weaviate, Milvus), and knowledge bases, with familiarity in integrating them with LLMs.
- Experience with advanced model monitoring, observability, and governance of LLMs and generative AI systems.
- Experience with data engineering or analytics platforms.
- Understanding of AI safety, security, and compliance best practices in production.
- Enthusiasm for learning and adopting the latest MLOps and AI technologies.
About Us
J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world\'s most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives.
We recognize 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, 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. Visit our FAQs for more information about requesting an accommodation.
About the Team
Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we\'re setting our businesses, clients, customers and employees up for success. #J-18808-Ljbffr
Mid-Level Machine Learning Engineer - Data Engineer II - Chase in London employer: Jpmorgan Chase & Co.
At Chase UK, we pride ourselves on fostering a dynamic work environment that encourages innovation and collaboration. As a Mid-Level Machine Learning Engineer, you'll be part of a forward-thinking team that values your contributions and offers ample opportunities for professional growth in the rapidly evolving field of AI and machine learning. With a commitment to diversity and inclusion, we ensure that every employee feels valued and empowered to make a meaningful impact in redefining digital banking.
StudySmarter Expert Advice🤫
We think this is how you could land Mid-Level Machine Learning Engineer - Data Engineer II - Chase in London
✨Tip Number 1
Familiarise yourself with the specific machine learning frameworks and tools mentioned in the job description, such as Transformers and LangChain. Having hands-on experience or projects that showcase your skills with these technologies can set you apart from other candidates.
✨Tip Number 2
Engage with the community around large language models and generative AI. Participate in forums, attend webinars, or contribute to open-source projects. This not only enhances your knowledge but also demonstrates your passion for the field when you network or interview.
✨Tip Number 3
Showcase your understanding of cloud-native environments by discussing any relevant projects where you've deployed ML solutions on platforms like AWS, GCP, or Azure. Be prepared to explain the challenges you faced and how you overcame them.
✨Tip Number 4
Highlight your collaborative skills by sharing examples of how you've worked in cross-functional teams. Emphasise your ability to engage in technical discussions and contribute to design reviews, as teamwork is crucial in this role.
We think you need these skills to ace Mid-Level Machine Learning Engineer - Data Engineer II - Chase in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights relevant experience in machine learning, Python programming, and any specific tools mentioned in the job description, such as Docker or Terraform. Use keywords from the job listing to ensure your application stands out.
Craft a Compelling Cover Letter:In your cover letter, express your passion for machine learning and how your skills align with Chase's mission of redefining digital banking. Mention specific projects or experiences that demonstrate your ability to deploy and maintain LLMs in production environments.
Showcase Your Projects:If you have worked on relevant projects, either professionally or personally, include them in your application. Describe your role, the technologies used, and the impact of the project. This will help illustrate your hands-on experience and problem-solving skills.
Highlight Collaboration Skills:Since the role involves working with cross-functional teams, emphasise your experience in collaborative environments. Provide examples of how you've successfully worked with data engineers, scientists, or product owners to achieve common goals.
How to prepare for a job interview at Jpmorgan Chase & Co.
✨Showcase Your Python Skills
As a Mid-Level Machine Learning Engineer, you'll need to demonstrate your proficiency in Python. Be prepared to discuss your past projects and how you've used Python for ML tooling and orchestration. Consider bringing examples of your code or discussing specific challenges you overcame.
✨Understand LLMs and Generative AI
Since the role involves deploying large language models, make sure you can talk about your experience with LLMs like GPT or Llama. Familiarise yourself with frameworks such as Transformers and LangChain, and be ready to explain how you've operationalised these technologies in previous roles.
✨Discuss Infrastructure as Code
The job requires knowledge of infrastructure as code tools like Terraform or CloudFormation. Be prepared to discuss how you've implemented IaC in your past projects, including any challenges faced and how you ensured scalability and reliability in your deployments.
✨Emphasise Collaboration and Agile Experience
Collaboration is key in this role, so highlight your experience working in cross-functional teams. Discuss your familiarity with agile methodologies and how you've contributed to team growth, whether through mentoring or participating in design reviews.
