Applied ML and Generative AI Leader - Executive Director

As an Applied ML and Generative AI leader within our Corporate Technology team, you will develop applications and provide tech support for all our corporate functions across our network. You will operate as a hands-on leader responsible for designing, building, and running production-grade ML and Generative AI services, while setting technical direction that scales across multiple workstreams. You will remain close to the code and architecture decisions, establish delivery and engineering standards, and ensure solutions meet enterprise expectations for security, stability, and operational rigor.

A core requirement is stakeholder partnership: you will routinely explain what is being built, why it matters, and how it will perform in production to both technical and non-technical audiences, enabling informed decisions and clear delivery alignment.

• Provide hands-on technical leadership by designing, developing, and deploying

ML/LLM/GenAI solutions from concept through production, maintaining ownership for reliability and operability once deployed

• Work closely with product managers, data scientists, ML engineers, and other

stakeholders to understand requirements and prioritize use cases.

• Mentor and uplift junior engineers through design reviews, code reviews,

pairing, and coaching, raising engineering quality and delivery discipline across the team. You will build and institutionalize MLOps capabilities, including automated pipelines for deployment, monitoring, and model lifecycle management, with emphasis on scalability and reliability

• Implement optimization strategies to fine-tune generative models for specific

NLP use cases, ensuring high-quality outputs in summarization and text generation.

• Conduct thorough evaluations of generative models (e.g., GPT-4.1), iterate on

model architectures, and implement improvements to enhance overall performance in NLP applications.

• Implement monitoring mechanisms to track model performance in real-time and

ensure model reliability.

• Communicate AI/ML/LLM/GenAI capabilities and results to both technical and

non-technical audiences. Stay informed about the latest trends and advancements in the latest AI/ML/LLM/GenAI research, implement cutting-edge techniques, and leverage external APIs for enhanced functionality.

• Bachelor's or Master's degree in Computer Science, Engineering, or a related

field and 10+ years of engineering experience, including 3+ years building, deploying, and operating applied AI/ML systems in production (model lifecycle, MLOps, monitoring, and governance).

• Demonstrate hands-on engineering leadership: setting technical direction,

making architecture decisions, conducting design and code reviews, mentoring junior engineers, and guiding implementation quality across multiple workstreams

• Proficiency in programming languages like Python for model development,

experimentation, and integration with OpenAI API.

• Experience with machine learning frameworks, libraries, and APIs, such as

TensorFlow, PyTorch, Scikit-learn, and OpenAI API.

• Experience with cloud computing platforms (e.g., AWS, Azure, or Google Cloud

Platform), containerization technologies (e.g., Docker and Kubernetes), and microservices design, implementation, and performance optimization.

• Solid understanding of fundamentals of statistics, machine learning (e.g.,

classification, regression, time series, deep learning, reinforcement learning), and generative model architectures, particularly GANs, VAEs.

• Ability to identify and address AI/ML/LLM/GenAI challenges, implement

optimizations and fine-tune models for optimal performance in NLP applications.

• A portfolio showcasing successful applications of generative models in NLP

projects, including examples of utilizing OpenAI APIs for prompt engineering.

• Familiarity with the financial services industries.
• Strong collaboration skills to work effectively with cross-functional teams,

communicate complex concepts, and contribute to interdisciplinary projects.

• Expertise in designing and implementing pipelines using Retrieval-Augmented

Generation (RAG).

• Hands-on knowledge of Chain-of-Thoughts, Tree-of-Thoughts, Graph-of-Thoughts

prompting strategies.

JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world’s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility.

These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.

Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we’re setting our businesses, clients, customers and employees up for success.