
Global financial services firm
AI/ML Engineer – Agentic Private Bank Engineer , Vice President
必备技能
Python
PyTorch
TensorFlow
This is a rare opportunity to help shape the future of our Private Bank. With the sponsorship from the CEO and the heads of the business, our goal is to create **an Agentic Private Bank -**reimagining the entire process from start to finish, rethinking the operating model including organizational structures and developing AI agents equipped with the latest tools and technologies to fundamentally reshape how we perform this business.
Join our dynamic team of innovators and technologists as an Applied AI/ML Lead, where your mission will be to revolutionize how the Bank services and advises clients, deepen client engagements, and drive process transformation. You will lead efforts to analyze existing processes and vast amounts of data to design autonomous AI agents. We seek leaders passionate about leveraging advanced data analysis, statistical modeling, and AI/ML techniques to solve complex business challenges through high-quality, cloud-centric software delivery. Our culture thrives on experimentation, continuous improvement, and learning. You will work in a collaborative, trusting, and intellectually stimulating environment—one that values diversity of thought and fosters creative solutions that serve the best interests of our global clientele.
J ob Responsibilities
- Lead the development and implementation of GenAI and Agentic AI solutions using Python to enhance automation and decision-making processes.
- Oversee the design, deployment, and management of prompt-based models on LLMs for various NLP tasks in the financial services domain.
- Conduct and guide research on prompt engineering techniques to improve the performance of prompt-based models within the financial services field, exploring and utilizing LLM orchestration and agentic AI libraries.
- Collaborate with cross-functional teams to identify requirements and develop solutions to meet business needs within the organization.
- Communicate effectively with both technical and non-technical stakeholders, including senior leadership.
- Build and maintain data pipelines and data processing workflows for prompt engineering on LLMs utilizing cloud services for scalability and efficiency.
- Develop and maintain tools and frameworks for prompt-based model training, evaluation, and optimization.
- Analyze and interpret data to evaluate model performance and identify areas of improvement.
Required qualifications, capabilities, and skills
- PhD in a quantitative discipline, e.g. Computer Science, Electrical Engineering, Mathematics, Operations Research, Optimization, or Data Science Or an MS with at least 7 years of industry or research experience in the field.
- Hands-on experience in building Agentic AI solutions.
- Familiarity with LLM orchestration and agentic AI libraries.
- Strong programming skills in Python with experience in Py Torch or Tensor Flow.
- Experience building data pipelines for both structured and unstructured data processing.
- Experience in developing APIs and integrating NLP or LLM models into software applications.
- Hands-on experience with cloud platforms (AWS or Azure) for AI/ML deployment and data processing.
- Excellent problem-solving skills and the ability to communicate ideas and results to stakeholders and leadership in a clear and concise manner.
- Basic knowledge of deployment processes, including experience with GIT and version control systems.
- Hands-on experience with MLOps tools and practices, ensuring seamless integration of machine learning models into production environments.
Preferred qualifications, capabilities, and skills
- Familiarity with model fine-tuning techniques.
- Knowledge of financial products and services, including trading, investment, and risk management.
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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
10条评价
3.8
10条评价
工作生活平衡
3.5
薪酬
4.0
企业文化
3.8
职业发展
3.2
管理层
2.8
68%
推荐率
优点
Good benefits and compensation
Supportive colleagues and environment
Flexible work arrangements
缺点
Long hours and heavy workload
Management issues and lack of direction
High stress and expectations
薪资范围
44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
面试评价
4条评价
难度
3.0
/ 5
时长
14-28周
录用率
50%
体验
正面 25%
中性 75%
负面 0%
面试流程
1
Application Review
2
HR Screen
3
Hiring Manager Interview
4
In-person/Final Interview
5
Offer
常见问题
Behavioral/STAR
Past Experience
Culture Fit
Financial Knowledge
Case Study
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