Software Engineer - Artificial Intelligence and Machine Learning

Software Engineer II - AI/ML

You’re ready to gain the skills and experience needed to grow within your role and advance your career — and we have the perfect software engineering opportunity for you.

As a Software Engineer II at JPMorgan Chase within the Consumer & Community Banking Team, you are part of an agile team that works to enhance, design, and deliver the software components of the firm’s state-of-the-art technology products in a secure, stable, and scalable way. As an emerging member of a software engineering team, you execute software solutions through the design, development, and technical troubleshooting of multiple components within a technical product, application, or system, while gaining the skills and experience needed to grow within your role.

Job responsibilities

 

• Executes standard software solutions, design, development, and technical troubleshooting
• Design, develop, and implement machine learning models and AI algorithms for various business applications.
• Applies knowledge of tools within the Software Development Life Cycle toolchain to improve the value realized by automation
• Applies technical troubleshooting to break down solutions and solve technical problems of basic complexity
• Monitor, maintain, and improve deployed models and AI systems.
• Stay updated with the latest advancements in AI/ML technologies and frameworks.
• Adds to team culture of diversity, opportunity, inclusion, and respect

 

 

Required qualifications, capabilities, and skills

 

• Formal training or certification on software engineering concepts and 2+ years applied experience
• Experience in developing and deploying machine learning models.
• Proficiency in programming languages such as Python, R, or Java.
• Experience with ML frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Strong understanding of data structures, algorithms, and statistical methods.
• Experience with data preprocessing, feature engineering, and model evaluation.
• Familiarity with cloud platforms (AWS, Azure, GCP) and MLOps practices is a plus.

Preferred qualifications, capabilities, and skills

• Experience with deep learning, NLP, computer vision, or reinforcement learning.
• Knowledge of big data technologies (Spark, Hadoop).
• Experience with RESTful APIs and microservices architecture.
• Prior experience in financial services or related industries.

Experience Level

Mid Level