JPMorgan ML Lead Software Engineer Data Platform 

United States, New Jersey, Jersey City 

698553990

Job responsibilities

• Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors
• Develops secure and high-quality production code, and reviews and debugs code written by others
• Drives decisions that influence the product design, application functionality, and technical operations and processes
• Serves as a function-wide subject matter expert in one or more areas of focus
• Actively contributes to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software Development Life Cycle
• Influences peers and project decision-makers to consider the use and application of leading-edge technologies
• Adds to the team culture of diversity, equity, inclusion, and respect

• Leads GenAI strategy and adoption: Spearheads generative AI initiatives, including chatbots and agentic architectures, aligned with business goals.

• Collaborates cross-functionally: Integrates ML solutions with data scientists, engineers, and stakeholders to enhance platform capabilities.

• Establishes ML lifecycle best practices: Develops standards for model development, deployment, monitoring, and maintenance.

• Mentors ML engineering team: Guides and develops the team, fostering continuous learning and innovation.

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience

• Hands-on practical experience delivering system design, application development, testing, and operational stability

• Advanced in one or more programming language(s)

• Advanced knowledge of software applications and technical processes with considerable in-depth knowledge in one or more technical disciplines (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
• Ability to tackle design and functionality problems independently with little to no oversight
• Practical cloud native experience
• Experience in Computer Science, Computer Engineering, Mathematics, or a related technical field

• Proven leadership in ML projects: Demonstrated ability to lead machine learning initiatives and drive strategic AI adoption.

• Expertise in GenAI technologies: In-depth knowledge of generative AI, LangChain, LangGraph, Autogen and other orchestration frameworks.

• Strong knowledge of MLFlow

• Solid understanding of system design and enterprise architecture patterns

• Experience in payments: Prior experience working in the financial services industry, particularly in payments or banking, with an understanding of industry-specific challenges and opportunities.

• GenAI Implementation Experience: Hands-on experience in implementing Generative AI solutions, such as chatbots or agentic architectures, in a production environment.

• Advanced Data Analytics Skills: Proficiency in advanced data analytics and statistical methods, with the ability to derive actionable insights from complex datasets.

• Certification in AI/ML