Take a technical leadership position within JPMorgan's Infrastructure Platform, where you'll harness cutting-edge AI techniques to revolutionize business decisions and workflow for cloud migration.

• As an Applied AI / ML Lead – Vice President
• Machine Learning Engineer at JPMorgan Infrastructure Platform, you will be at the forefront of combining cutting-edge AI techniques with the company's unique data assets to optimize business decisions and automate processes. You will have the opportunity to advance the state-of-the-art in AI as applied to financial services, leveraging the latest research from fields of Generative AI, Agentic AI, and statistical machine learning to revolutionize cloud migration. You will be instrumental in building products that automate processes, help experts prioritize their time, and make better decisions. We have a growing portfolio of AI–powered products and services and increasing opportunity for re-use of foundational components through careful design of libraries and services to be leveraged across the team. This role offers a unique blend of scientific research and software engineering, requiring a deep understanding of both mindsets. The role is initially that of an individual contributor.

Job responsibilities:

• Lead the deployment and scaling of advanced generative AI, agentic AI, and classical ML solutions.
• Design and execute enterprise-wide, reusable AI/ML frameworks and core infrastructure to accelerate AI solution development.
• Design and develop multi-agent systems for orchestration, agent-to-agent communication, eval, memory, telemetry, and guardrails.
• Apply context and prompt engineering techniques to improve prompt-based model performance.
• Develop and maintain tools and frameworks for prompt-based agent evaluation, monitoring, and optimization at enterprise scale.
• Build and maintain data pipelines and processing workflows for scalable, efficient data consumption.
• Write secure, high-quality production code and conduct code reviews.
• Partner with Engineering, Product, and Business teams to identify requirements and develop solutions.
• Communicate technical concepts and results to both technical and non-technical stakeholders, including senior leadership.
• Provide technical leadership, mentorship, and guidance to junior engineers, promoting a culture of excellence and continuous learning.

Required qualifications, capabilities, and skills:

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field.
• Experience in machine learning engineering.
• Strong proficiency in Python and experience deploying end-to-end pipelines on AWS.
• Hands-on experience in system design, application development, testing, and operational stability.

Preferred qualifications, capabilities, and skills:

• Strategic thinker with the ability to drive technical vision for business impact.
• Demonstrated leadership working with engineers, data scientists, and ML practitioners.
• Experience with AWS and infrastructure-as-code tools such as Terraform.
• Experience in multi-agent orchestration.
• Familiarity with MLOps practices, including CI/CD for ML, model monitoring, automated deployment, and ML pipelines.
• Experience with agentic telemetry and evaluation services.
• Experience in customising and optimizing Github Copilot using VSCode Extension or Model Context Protocol (MCP)