Asset Management - AI Engineer - Associate/vp

JPMorgan Chase · Banking · Shanghai, China · Asset & Wealth Management

AI Engineer role at JPMorgan Chase focusing on the research, deployment, and optimization of large models, including training, fine-tuning, and prompt engineering. The role involves implementing AI tools in enterprise business scenarios, developing AI platforms, and building AI workflows and agents. Requires strong algorithm and engineering capabilities with experience in RAG, Agent, LangChain, and large model training frameworks.

What you'd actually do

Responsible for the research, deployment, and optimization of large models, including training, fine-tuning, prompt word engineering, and private knowledge accumulation;
Undertake the implementation of large models and AI tools in enterprise business scenarios, and promote the deep integration of AI technology and business;
Responsible for the algorithm research and technical implementation of the enterprise AI platform, including model architecture design, hardware selection and deployment;
Responsible for AI Workflow, AI Agent development and tuning;
Undertake the overall architecture design of the AI platform to ensure system scalability, high performance, and high availability;

Skills

Required

Python
machine learning
deep learning
natural language processing (NLP)
large language models (LLM)
RAG
Agent
LangChain
PyTorch
ML
DL
NLP
multi-machine and multi-GPU solutions

Nice to have

Java
SQL
Shell
contributed to open source projects
published papers
experience in implementing AI platforms or enterprise-level AI solutions
English as a working language
financial industry experience

What the JD emphasized

more than 3 years of experience in AI-related fields
practical experience in RAG, Agent, LangChain and other technologies
experience in implementing AI platforms or enterprise-level AI solutions

Other signals

deployment and optimization of large models
implementation of large models and AI tools in enterprise business scenarios
AI platform
AI Workflow, AI Agent development and tuning
overall architecture design of the AI platform

Read full job description

Job Responsibilities:

Responsible for the research, deployment, and optimization of large models, including training, fine-tuning, prompt word engineering, and private knowledge accumulation;
Undertake the implementation of large models and AI tools in enterprise business scenarios, and promote the deep integration of AI technology and business;
Responsible for the algorithm research and technical implementation of the enterprise AI platform, including model architecture design, hardware selection and deployment;
Responsible for AI Workflow, AI Agent development and tuning;
Undertake the overall architecture design of the AI platform to ensure system scalability, high performance, and high availability;
Work closely with the business team to implement AI technology in actual business scenarios and realize business value;

Job requirements:

Bachelor degree or above in computer science, artificial intelligence, data science or related majors;
More than 3 years of experience in AI-related fields, with solid algorithm and engineering capabilities;
Familiar with core technologies such as machine learning, deep learning, natural language processing (NLP), and large language models (LLM);
Proficient in Python, and familiar with at least one programming language such as Java, SQL, Shell;
Have practical experience in RAG, Agent, LangChain and other technologies, and have experience in actual project implementation;
Familiar with common open source frameworks such as PyTorch, ML, DL, and NLP, and possess theoretical and practical skills in multi-machine and multi-GPU solutions based on large model training frameworks;
Possess a passion for technology and a responsible work attitude, and be enthusiastic about technological innovation and implementation; possess a strong passion for applying artificial intelligence technology to the asset management field to generate business value;
Candidates who have contributed to open source projects or published papers are preferred;
Candidates with experience in implementing AI platforms or enterprise-level AI solutions are preferred;
Having the ability to use English as a working language is preferred (optional);
Experience in the financial industry is preferred (not required).

Job Responsibilities:

Responsible for the research, deployment, and optimization of large models, including training, fine-tuning, prompt word engineering, and private knowledge accumulation;
Undertake the implementation of large models and AI tools in enterprise business scenarios, and promote the deep integration of AI technology and business;
Responsible for the algorithm research and technical implementation of the enterprise AI platform, including model architecture design, hardware selection and deployment;
Responsible for AI Workflow, AI Agent development and tuning;
Undertake the overall architecture design of the AI platform to ensure system scalability, high performance, and high availability;
Work closely with the business team to implement AI technology in actual business scenarios and realize business value;

Job requirements:

Bachelor degree or above in computer science, artificial intelligence, data science or related majors;
More than 3 years of experience in AI-related fields, with solid algorithm and engineering capabilities;
Familiar with core technologies such as machine learning, deep learning, natural language processing (NLP), and large language models (LLM);
Proficient in Python, and familiar with at least one programming language such as Java, SQL, Shell;
Have practical experience in RAG, Agent, LangChain and other technologies, and have experience in actual project implementation;
Familiar with common open source frameworks such as PyTorch, ML, DL, and NLP, and possess theoretical and practical skills in multi-machine and multi-GPU solutions based on large model training frameworks;
Possess a passion for technology and a responsible work attitude, and be enthusiastic about technological innovation and implementation; possess a strong passion for applying artificial intelligence technology to the asset management field to generate business value;
Candidates who have contributed to open source projects or published papers are preferred;
Candidates with experience in implementing AI platforms or enterprise-level AI solutions are preferred;
Having the ability to use English as a working language is preferred (optional);
Experience in the financial industry is preferred (not required).