招聘
Join JPMorgan Chase and transform financial services with innovative AI. Be part of a world-class team driving real impact for millions of customers.
As a Applied AI ML Associate senior at JPMorgan Chase within the Consumer and Community Banking technology, you will provide technical leadership and strategic direction for the development and deployment of scalable, secure, and high-quality machine learning solutions. You will collaborate with cross-functional teams, guide best practices, and architect next-generation AI platforms that power the future of banking.
Job Responsibilities
- Provide technical guidance and direction to business units, engineering teams, contractors, and vendors.
- Serve as a subject matter expert in AI, machine learning, and related technologies.
- Advise executive leadership with strategic recommendations on machine learning initiatives.
- Design, develop, and maintain secure, high-quality production code.
- Review and debug code to ensure adherence to best practices and code quality.
- Champion software and model quality, integrity, and security across the organization.
- Influence product design, application functionality, and technical operations.
- Architect and oversee the development of advanced machine learning models and systems using cutting-edge technologies.
- Ensure platforms support complex use cases, including real-time predictions, big data processing, and advanced analytics.
- Drive innovation in machine learning, ensuring solutions are scalable, flexible, and future-proof.
- Advocate for firmwide frameworks, tools, and SDLC best practices within the engineering community.
Required Qualifications, Capabilities, and Skills
- Formal training or certification in software engineering concepts with 3+ years of applied experience.
- Proven technical leadership and experience guiding engineering teams.
- Expertise in developing, reviewing, and debugging secure, high-quality production code.
- Deep knowledge of machine learning, big data processing, and advanced analytics.
- Experience architecting scalable and flexible machine learning platforms.
- Demonstrated ability to drive innovation and influence technology adoption.
- Excellent communication skills, with the ability to advise and influence executive leadership.
- Technical proficiency in Python for software and model development, AWS Cloud for scalable solution deployment. Retrieval-Augmented Generation (RAG) and AI/Agents, Natural Language Understanding (NLU), Natural Language Processing (NLP), and Large Language Models (LLM)
- Experience with engineering and operational best practices ML Ops for operationalizing machine learning workflows, CI/CD pipelines for continuous integration and delivery, SDLC best practices for software development lifecycle management
Preferred Qualifications, Capabilities, and Skills
- Experience in the financial services industry, especially in consumer and community banking.
- Familiarity with firmwide frameworks, tools, and SDLC best practices.
- Track record of contributing to the engineering community and promoting best practices.
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关于JPMorgan Chase

JPMorgan Chase
PublicJPMorgan Chase & Co. is an American multinational banking institution headquartered in New York City and incorporated in Delaware. It is the largest bank in the United States, and the world's largest bank by market capitalization as of 2025.
300,000+
员工数
New York City
总部位置
$500B
企业估值
评价
3.8
10条评价
工作生活平衡
3.2
薪酬
4.1
企业文化
3.8
职业发展
3.0
管理层
2.5
65%
推荐给朋友
优点
Good benefits and compensation
Supportive and collaborative environment
Flexible work arrangements
缺点
Long hours and heavy workload
Management issues and lack of direction
High stress during peak times
薪资范围
41个数据点
Mid/L4
Senior/L5
Mid/L4 · Applied AI ML Associate
2份报告
$188,500
年薪总额
基本工资
$145,000
股票
-
奖金
-
$182,000
$195,000
面试经验
5次面试
难度
3.0
/ 5
时长
14-28周
录用率
40%
体验
正面 20%
中性 80%
负面 0%
面试流程
1
Application Review
2
HireVue Video Interview
3
Recruiter Screen
4
Superday/Panel Interview
5
Final Interview
6
Offer
常见问题
Behavioral/STAR
Technical Knowledge
Culture Fit
Past Experience
Case Study
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