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JPMorgan ML Lead Software Engineer Data Platform 
United States, New Jersey, Jersey City 
698553990

Today

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

Preferred capabilities and skills
  • 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