Job Description
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
