At a Glance
- Tasks: Help build and deploy AI/ML models in a safe, scalable way.
- Company: Join J.P. Morgan, a global leader in financial services.
- Benefits: Competitive salary, diverse culture, and opportunities for growth.
- Other info: Diverse team with a focus on inclusion and professional development.
- Why this job: Make an impact with cutting-edge AI/ML technology in a dynamic environment.
- Qualifications: Experience in AI/ML products and strong software engineering skills required.
The predicted salary is between 70000 - 90000 £ per year.
As a Senior Associate, Applied AI/ML Engineer in the Applied AI/ML team, you will help customers build, deploy, and operate AI/ML models and agentic systems in a safe, scalable way.
Job responsibilities:
- Assist customers in building and deploying models and agents across multiple model/agent frameworks (selection, integration patterns, troubleshooting, best practices).
- Implement and operate AI/ML observability: experimentation management, tracing, and monitoring to improve quality and reliability of model/agent behaviour.
- Build and optimize large-scale data processing pipelines and feature workflows using distributed compute (e.g., Ray, Spark, or similar).
- Develop AI/ML systems using coding assistants to improve engineering efficiency while maintaining code quality standards.
- Ensure secure deployment and access for AI/ML services (e.g., secure-by-design practices, access controls, and environment separation), aligned to firm guidance for safe/responsible AI use.
- Produce clear technical documentation and runbooks to enable supportability and repeatable delivery.
Required qualifications, capabilities, and skills:
- Hands-on experience supporting customers/teams delivering AI/ML products (model + agent workflows).
- Experience with observability, evaluation/experimentation, and tracing platforms for AI/ML or LLM/agent systems.
- Experience with distributed data processing at scale (Ray, Spark, or similar).
- Strong software engineering skills (clean code, testing, CI/CD concepts, API/service development).
- Strong communication skills and ability to translate requirements into practical engineering outcomes.
Preferred qualifications:
- Experience integrating AI/ML into production systems (monitoring, incident response, change management).
- Familiarity with responsible AI/ML governance expectations and lifecycle controls.
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.
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.
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We think you need these skills to ace Applied AI ML Engineer (Bournemouth)
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Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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