This is your chance to change the path of your career and guide multiple teams to success at one of the world's leading financial institutions.

As a Manager of Software Engineering at JPMorgan Chase within the Consumer and Community Banking – CAMP Technology, you lead multiple teams and manage day-to-day implementation activities by identifying and escalating issues and ensuring your team’s work adheres to compliance standards, business requirements, and tactical best practices.

Job responsibilities

• Responsible for setting direction, development, and implementation of  ML and GenAI driven solutions
• Develop and implement machine learning models and algorithms to solve complex business and operational use cases.
• Design and deploy generative AI applications to automate and optimize business processes.
• Write production-grade code for both training and inference functions
• Collaborate with Machine Learning engineers, product managers, key business stakeholders, engineering, and platform partners to deploy projects that deliver cutting-edge machine learning-driven digital solutions.
• Collaborate with MLOps engineers in developing and testing the training and inference applications under the production architecture blueprint, often in integration with upstream and downstream applications.
• Drive end-to-end system architecture in collaboration with ML, MLOps, and Architecture leads.
• Ensure the scalability and reliability of AI/ML solutions in a production environment.
• Stay up-to-date with the latest advancements in AI/ML technologies and integrate them into our operations.
• Mentor Junior Machine Learning associates in delivering successful projects and building successful careers in the firm.

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 5+ years applied experience. In addition, demonstrated coaching and mentoring experience 
• Proven experience in deploying AI/ML applications in a production environment, with skills in deploying models on AWS platforms such as SageMaker or Bedrock.
• Familiarity with MLOps practices, encompassing the full cycle from design, experimentation, deployment, to monitoring and maintenance of machine learning models.
• Expertise in machine learning frameworks such as TensorFlow, PyTorch, Pytorch Keras, or Scikit-learn.
• Proficiency in programming languages such as Python, Java etc.
• Proficiency in writing comprehensive test cases, with a strong emphasis on using testing frameworks such as pytest to ensure code quality and reliability.
• Experience with generative AI models, including GANs, VAEs, or transformers. 
• Solid understanding of data preprocessing, feature engineering, and model evaluation techniques.
• Familiarity with cloud platforms (AWS) and containerization technologies (Docker, Kubernetes, Amazon EKS).
• Provide overall direction, oversight, and coaching for a team of entry-level to mid-level software engineers that work on basic to moderately complex tasks
• Creates a culture of diversity, equity, inclusion, and respect for team members and prioritizes diverse representation.

Preferred qualifications, capabilities, and skills

• Experience leading teams of ML Engineers and technologists .
• Ability to guide and coach teams on approach to achieve goals aligned against a set of strategic initiatives.
• Experience with hiring, developing, and recognizing talent.
• Excellent problem-solving skills and the ability to work independently and collaboratively.
• Strong communication skills to effectively convey complex technical concepts to non-technical stakeholders.
• Experience in using GenAI (OpenAI or AWS Bedrock) to solve business problem.
• Experience with large scale training, validation and testing