Applied Machine Learning and Generative AI Lead
Real job — pulled straight from JPMorgan Chase’s careers page · Verified July 15, 2026 · No reposts.
Job description
JPMorgan Chase is hiring a Applied Machine Learning and Generative AI Lead — a full-time, based in Jersey City, NJ role. Apply directly on JPMorgan Chase's careers page below.
Applied ML and Generative AI Lead - Vice President
Location: Jersey City, NJ, United States
.P. Morgan is a global leader in financial services, providing strategic advice and products to the world’s most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives.
As the Applied ML and Generative Lead within J.P.Morgan, you will operate as a hands-on engineering 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.
Job responsibilities
- 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.
Required qualifications, capabilities, and skills
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field and 7+ years of demonstrated experience in applied AI/ML engineering, with a track record of developing and deploying business critical machine learning models in production.
- 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.
Preferred qualifications, capabilities, and skills
- Familiarity with the financial services industries.
- 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.
- Strong collaboration skills to work effectively with cross-functional teams, communicate complex concepts, and contribute to interdisciplinary projects.
About Us
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.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans
About the Organization
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.Promote evolving technology needs and strengthen our technology controls as a key member of a high impact team.Get Applied Machine Learning and Generative AI Lead jobs like this→
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Frequently asked questions
What skills are required for Applied Machine Learning and Generative AI Lead at JPMorgan Chase?
The required skills for Applied Machine Learning and Generative AI Lead at JPMorgan Chase include: Python, TensorFlow, PyTorch, Scikit-learn, OpenAI, AWS, Azure, GCP, Docker, Kubernetes, Microservices, Machine Learning, Deep Learning, Generative AI, NLP.
What is the seniority level for Applied Machine Learning and Generative AI Lead at JPMorgan Chase?
Applied Machine Learning and Generative AI Lead at JPMorgan Chase is a Manager / Principal level position.
How do I apply for Applied Machine Learning and Generative AI Lead at JPMorgan Chase?
You can view the full description and apply for Applied Machine Learning and Generative AI Lead at JPMorgan Chase on EchoJobs: https://echojobs.io/job/jpmorgan-chase-applied-ml-and-generative-ai-lead-vice-president-6r6qy.