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About JPMorgan Chase
JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.
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As an Applied Artificial Intelligence Machine Learning Lead - Vice President on the Asset and Wealth Management AI Engineering team, you will serve as a seasoned leader and hands-on engineer. You will be responsible for designing and implementing scalable data processing pipelines, developing cutting-edge machine learning and LLM models, and deploying these solutions into production environments on AWS or Azure. Your daily work involves building high-impact business solutions through data analysis and creating robust model inference services to solve complex problems for Private Bank clients. Required skills include Python programming, deep knowledge of data structures, algorithms, and statistics, along with experience using OpenAI or Anthropic models. You will also utilize SQL and NoSQL stores like Postgres, OpenSearch, and Redis while potentially leveraging JavaScript, TypeScript, Go, or Rust to build full-stack products in the financial services industry.
Architect and implement lighthouse machine learning and LLM-powered solutions.
Develop and productionize high-quality machine learning models and services to drive business impact.
Design and implement highly scalable and reliable data processing pipelines.
Deploy model inference services and AI solutions into public cloud infrastructure like AWS or Azure.
Perform end-to-end solution design with a focus on modern architecture, scalability, and security.
Manage data models and real-time data processing using SQL and NoSQL stores.
Develop full-stack products utilizing modern JavaScript and TypeScript frameworks.
What we're looking for
MS in Computer Science, Statistics, Mathematics, or Machine Learning.
Minimum 7 years of development experience with at least 4 years working on AI solutions.
Experience using LLMs to solve business problems including tracing, evaluations, and guardrails.
Strong programming skills in Python and deep knowledge of Data Structures, Algorithms, Machine Learning, Data Mining, Information Retrieval, and Statistics.
Demonstrated ability to perform independent end-to-end solution design with a focus on modern architecture, scalability, and security.
Knowledge of data management including model design and real-time processing on SQL (Postgres) and NoSQL (OpenSearch, Redis).
Proven leadership capacity for AI/ML idea generation and excellent communication skills with technical and business partners.
Experience in finance, LLM fine-tuning, full-stack development (Next.js, Svelte), high-performance languages (Go, Rust), or cloud platforms (AWS, Azure, Kubernetes) are preferred.
Machine Learning
Deep Learning
Generative AI
LLMs
NLP
Python
Java
C++
Transformers
Hugging Face
TensorFlow
PyTorch
NumPy
Scikit-Learn
Pandas
AWS
SageMaker
Prompt Engineering
Big Data
LLMs
Agentic AI
RAG
Knowledge Graphs
Python
PyTorch
TensorFlow
Reinforcement Learning
NLP
Speech Analytics
Time Series
Recommendation Systems
Data Science
Data Science
Artificial Intelligence
Machine Learning
Agentic AI
NLP
LLMs
RAG
Big Data
Python
PySpark
Excel
Microsoft Office
Semantic Searching
Financial Forecasting