JPMorgan Chase

posted 3 months ago

Full-time - Mid Level
Credit Intermediation and Related Activities

About the position

Join our team as a Machine Learning Software Engineer and play a pivotal role in shaping the future of Machine Learning and AI solutions within the Consumer & Community Banking sector at JPMorgan Chase. As a Machine Learning Software Engineer at JPMorgan Chase within the Consumer & Community Banking, Operations team, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firm's business objectives. In this role, you will execute creative software solutions, design, development, and technical troubleshooting with the ability to think beyond routine or conventional approaches to build solutions or break down technical problems. You will develop secure high-quality production code, review and debug code written by others, and identify opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems. Additionally, you will contribute to a team culture of diversity, equity, inclusion, and respect. Your responsibilities will also include developing and implementing machine learning models to solve complex business problems and enhance ML-driven applications, optimizing machine learning models for performance and scalability leveraging cloud-based resources, and demonstrating self-promotion and the ability to continuously learn and stay updated with the latest AI and machine learning advancements. You will troubleshoot and debug machine learning-related issues, initiate and contribute to AI strategy, and serve as the technical liaison between business, product, data scientists, and engineers, playing a key role in our innovation and transformation roadmap.

Responsibilities

  • Execute creative software solutions, design, development, and technical troubleshooting.
  • Develop secure high-quality production code, and review and debug code written by others.
  • Identify opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems.
  • Add to team culture of diversity, equity, inclusion, and respect.
  • Develop and implement machine learning models to solve complex business problems and enhance ML-driven applications.
  • Optimize machine learning models for performance and scalability leveraging cloud-based resources.
  • Demonstrate self-promotion and ability to continuously learn and stay updated with latest AI and machine learning advancements.
  • Troubleshoot and debug machine learning related issues.
  • Initiate and contribute to AI strategy.
  • Be the technical liaison between business, product, data scientists and engineers.

Requirements

  • Formal training or certification on software engineering concepts and 3+ years of applied experience.
  • Hands-on practical experience delivering system design, application development, testing, and operational stability.
  • Advanced in one or more programming language(s).
  • Solid experience with Python, SQL, CI/CD pipeline, Github, AWS or Azure or GCP required.
  • Proven track record in developing machine learning models at scale from inception to business impact on a cloud platform.
  • Strong understanding of various machine learning algorithms, including supervised and unsupervised learning, neural networks and reinforcement learning.
  • Hands-on experience in optimizing LLM prompt.
  • Strong end-to-end working knowledge on how a machine learning product is built.
  • Familiarity with MLOPS and components in MLOPS ecosystem.
  • Good understanding of agile methodologies.
  • Excellent communication and presentation skills.

Nice-to-haves

  • In-depth knowledge of the financial services industry and their IT system.
  • Practical AWS or Azure cloud native experience.
  • Experience in data streaming tools such as Kafka.
  • Experience with Generative AI and LLM.

Benefits

  • Comprehensive health care coverage
  • On-site health and wellness centers
  • Retirement savings plan
  • Backup childcare
  • Tuition reimbursement
  • Mental health support
  • Financial coaching
  • Discretionary incentive compensation based on individual achievements and contributions.
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