Lead Software Engineer - AI/ML

Global financial services firm offering banking, investment, and technology solutions.
Machine Learning
Staff Software Engineer
In-Person
5,000+ Employees
5+ years of experience
AI · Finance

Description For Lead Software Engineer - AI/ML

Join JPMorgan Chase's Consumer and Community Banking – CAMP Technology team as a Lead Software Engineer, where you'll be at the forefront of AI/ML innovation. This role combines technical leadership with hands-on development of cutting-edge machine learning and LLM models. You'll work within an agile team environment, focusing on enhancing and building trusted market-leading technology products. The position offers the opportunity to work with state-of-the-art AI technologies, including GenAI and LLMs, while solving complex business problems through data analysis. You'll be responsible for deploying and supporting production-grade models on AWS or Azure, mentoring team members, and driving innovation in AI/ML solutions. This role is perfect for experienced engineers who want to impact financial technology while working with the latest AI advancements in a global organization. The position offers the chance to work on meaningful projects that directly influence banking technology solutions while being part of a collaborative, forward-thinking team.

Last updated 17 days ago

Responsibilities For Lead Software Engineer - AI/ML

  • Setting direction, development, and implementation of ML and GenAI driven solutions
  • Develop and implement machine learning models and algorithms
  • Design and deploy generative AI applications
  • Conduct research on prompt engineering techniques
  • Analyze large datasets to extract actionable insights
  • Ensure scalability and reliability of AI/ML solutions
  • Collaborate with cross-functional teams
  • Mentor and guide junior team members

Requirements For Lead Software Engineer - AI/ML

Python
Java
Kubernetes
  • 5+ years applied software engineering experience
  • Experience in deploying AI/ML applications in production environment
  • Proficiency in Python, Java and other programming languages
  • Experience with MLOps practices
  • Hands-on experience with machine learning frameworks
  • Proficiency in writing comprehensive test cases
  • Experience with generative AI models
  • Knowledge of cloud platforms (AWS) and containerization
  • Strong problem-solving skills

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