Job description

If you are looking for a game-changing career, working for one of the world's leading financial institutions, you’ve come to the right place. As a Principal Software Engineer at JPMorgan Chase within the Corporate AI/ML Data Platforms Team, you will bring your expertise and engineering excellence to an agile team, focusing on enhancing, building, and delivering trusted, market-leading technology products in a secure, stable, and scalable manner. You will leverage your advanced technical skills and collaborate with colleagues across the organization to achieve best-in-class outcomes across various technologies, supporting one or more of the firm’s portfolios. Job responsibilities • Creates complex and scalable coding frameworks using appropriate software design frameworks • Develops secure and high-quality production code, and reviews and debugs code written by others • Advises cross-functional teams on technological matters within your domain of expertise • Serves as the function’s go-to subject matter expert • Contributes to the development of technical methods in specialized fields in line with the latest product development methodologies • Creates durable, reusable software frameworks that are leveraged across teams and functions • Influences leaders and senior stakeholders across business, product, and technology teams • Champions the firm’s culture of diversity, opportunity, inclusion, and respect • Lead the development of the next generation AI/ML-features for training and experimentation across traditional and gen AI that are tailored towards data scientists and ML/AI engineers. • Elevate the overall engineering and applied science culture and practices across the organization and the firm. • Represent the organization through external and internal talks and conferences. Required qualifications, capabilities, and skills • Formal training or certification on software engineering concepts and 10+ years applied experience • Hands-on practical experience delivering system design, application development, testing, and operational stability • Expert in one or more programming language(s) • Advanced knowledge of software application development and technical processes with considerable in-depth knowledge in one or more technical disciplines (e.g., cloud, artificial intelligence, machine learning, mobile, etc.) • Experience applying expertise and new methods to determine solutions for complex technology problems in one or more technical disciplines • Experience leading a product as a Product Owner or Product Manager • Ability to present and effectively communicate with Senior Leaders and Executives • Understanding of the business • Practical cloud native experience • Experience in Computer Science, Computer Engineering, Mathematics, or a related technical field • 5 years of experience working with Machine Learning, AI, Large Language Models (LLM) infrastructure, especially with training, model development, and other requests. Preferred qualifications, capabilities, and skills • M.Sc or Ph.D in CS or any related field. • Expertise in Machine Learning frameworks like Python, Scikit-learn, PyTorch, TensorFlow, Apache Spark, and experience with Generative AI models like GANs, Transformers, and Diffusion Models. • Knowledge of MLOps best practices around model training, evaluation, deployment, and governance. Ability to communicate and help clients operationally set up MLOps functions. • Experience integrating ML solutions with cloud platforms like AWS SageMaker, GCP Vertex AI, Azure Cognitive Services, and leveraging their pre-built capabilities. • Proficiency in ML workflow tools like Kubeflow and MLflow for experiment tracking, model management, and model serving. • Ability to identify and articulate the business value of AI/ML to stakeholders using innovative techniques like AI Readers, AI Assistants, Agentic frameworks, etc • Passion for AI/ML and ability to stay updated on the latest advancements through conferences, publications, cohorts, etc. Experience in consulting, sales engineering, and/or customer success.

Requirements