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Home Lending Data & Analytics – Applied AI/ML Engineer - VP
Jacksonville, FL, United States, US
·
On-site
·
Full-time
·
1w ago
Are you ready to play a pivotal role in shaping the future of Data & Analytics?
As a valued member of our Home Lending Data & Analytics Applied AI/ML team, you will be at the forefront of our firm-wide initiatives to innovate and enhance Data & Analytics functions. Your contributions will be instrumental in transforming the processes and tools for data, analysis, and modeling.
As an Applied AI/ML Engineer within our Home Lending Data & Analytics team, you will work in close coordination with various teams in Data & Analytics, including Data Owners, Reporting, Analysis, and Modeling. Your role will involve designing and implementing AI-powered solutions that boost operational efficiency, improve employee experience, and improve data quality. Leveraging your expertise in artificial intelligence and data analytics, you will develop state-of-the-art applications that simplify processes and yield tangible business outcomes. Your valuable contributions will play a pivotal role in transforming our way of working, ensuring we remain at the cutting edge of the industry.
Job Responsibilities:
- Write and deliver high-quality code for AI-driven Home Lending Data & Analytics initiatives, ensuring robust and efficient solutions that meet business objectives
- Work closely with Data Owners, Reporting, Analysis, and Modeling teams to address and solve complex problems including AI, ML, and advanced analytics, with a focus on generative AI technologies
- Deploy and scale AI models to production environments, ensuring robustness, reliability, security, and compliance
- Fine-tune AI models for optimal performance and efficiency, addressing any issues that arise
- Work closely with data scientists, software engineers, and product teams to integrate AI solutions into existing systems and workflows
- Own and manage the entire code lifecycle, from development through production deployment and ongoing maintenance, adhering to best practices
- Develop and maintain comprehensive technical documentation for all AI solutions, ensuring clarity, accuracy, and accessibility for both technical and non-technical stakeholders
- Continuously monitor AI performance, making necessary adjustments to maintain and improve accuracy and efficiency
- Engage with stakeholders to develop, demonstrate, and iterate on deliverables, ensuring alignment with analyst needs and regulatory requirement
Required qualifications, capabilities, and Skills:
- 7+ years of work experience.
- Masters degree in a quantitative field such as Data Science, Computer Science, Engineering, Math, Physics, etc
- Proven track record of delivering projects in the AI/ML and data analytics space
- Proficiency in Python.
- Experience with foundation LLMs (e.g., GPT-5, Claude), RAG, Agents.
- Strong understanding of software engineering principles and practices, including version control, testing, and code optimization
- Technical documentation experience preferred.
Preferred qualifications, capabilities and skills:
- Experience with AWS Cloud Platform and Databricks for deploying and managing machine learning models preferred.
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About JPMorgan Chase

JPMorgan Chase
PublicJPMorgan Chase is a multinational investment bank and financial services company that provides banking, investment, and asset management services globally. It is one of the largest banks in the United States by assets and market capitalization.
300,000+
Employees
New York City
Headquarters
Reviews
4.2
10 reviews
Work Life Balance
4.2
Compensation
4.3
Culture
4.5
Career
4.4
Management
4.1
75%
Recommend to a Friend
Pros
Good pay and benefits
Work-life balance
Career advancement opportunities
Cons
Heavy workload at times
Career advancement takes time
Pay could be better in some roles
Salary Ranges
47 data points
Mid/L4
Senior/L5
Mid/L4 · Applied AI ML Associate
2 reports
$188,500
total / year
Base
$145,000
Stock
-
Bonus
-
$182,000
$195,000
Interview Experience
4 interviews
Difficulty
2.8
/ 5
Duration
14-28 weeks
Interview Process
1
Application Review
2
HireVue Video Interview
3
Technical/Behavioral Assessment
4
Final Interview Round
5
Offer Decision
Common Questions
Behavioral/STAR
Technical Knowledge
Past Experience
Culture Fit
Case Study
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