Applied AI ML Senior Associate
JPMorgan Chase18 hours ago
Base Salary
$138k - $195k/yr
Responsibilities
- Build generative AI, agentic AI, and large language model solutions in Python from proof of concept through production deployment.
- Design context engineering approaches to improve model accuracy, latency, reliability, and user experience.
- Lead enterprise semantic modeling strategy, including ontology standards, governance, and lifecycle management.
- Create scalable ontologies representing business entities, relationships, rules, and constraints with domain experts.
- Define semantic integration patterns across data pipelines, APIs, data contracts, and experience layers.
- Establish and govern a unified semantic layer for analytics, machine learning, and transactional systems.
- Enable AI agents and intelligent workflows using ontology-driven context, semantic reasoning, and orchestration.
- Build and maintain pipelines and frameworks for model training, evaluation, optimization, monitoring, and machine learning operations.
- Implement responsible AI practices, model risk controls, and governance for regulated environments.
- Mentor engineers and data scientists and influence technical direction through engineering rigor, reuse, and continuous improvement.
Requirements
- Master’s degree in a data science-related discipline and eight years of industry experience, or a PhD in a data science-related discipline.
- Experience developing and deploying machine learning and generative AI solutions using Python.
- Ability to write and maintain production-quality code with documentation and maintainable design patterns.
- Experience with automated testing, including unit tests, and continuous integration pipelines.
- Experience building and managing data pipelines and processing workflows for analytics and machine learning.
- Strong scientific thinking, structured problem solving, hypothesis-driven analysis, and metric definition.
- Strong written and verbal communication skills for technical and non-technical stakeholders.
- Ownership and attention to detail in ambiguous and complex problem spaces.
- Ability to work independently while collaborating across product, engineering, data, and business teams.
- Preferred experience designing or governing semantic models and ontologies, including taxonomy design and lifecycle governance.
- Preferred experience with retrieval-augmented generation, tool use, and evaluation strategies for large language model applications.
- Familiarity with responsible AI techniques such as bias testing, explainability, and model monitoring.
- Experience designing scalable real-time or near-real-time inference architectures and intelligent workflow orchestration.
- Experience influencing cross-functional technical direction and mentoring engineers through design reviews and delivery execution.
Benefits
- Competitive total rewards and benefits package, with eligibility-based health care coverage, on-site wellness centers, retirement savings, backup childcare, tuition reimbursement, mental health support, and financial coaching.
- Base salary and any applicable incentive compensation are determined by role, experience, skill set, location, and eligibility.
- JPMorganChase is an equal opportunity employer and provides reasonable accommodations.
- The role is part of the Corporate Technology Data Science and AI team supporting Corporate Functions.
Tech Stack
Categories
About JPMorgan Chase
JPMorgan Chase provides consumer and commercial banking, payments, credit card, wealth management, and corporate and investment banking services to individuals, businesses, institutions, and governments. The public company (NYSE: JPM) earns revenue from interest, fees, trading, and asset management across operations in more than 100 markets. Headquartered in New York City with roots dating to 1799, it serves retail customers and prominent corporate and government clients through brands including Chase and J.P. Morgan.