Applied AI ML Associate

You’re ready to gain the skills and experience needed to grow within your role and advance your career — and we have the perfect Applied AI ML opportunity for you.

As an Applied AI ML Associate at JPMorgan Chase within the Commercial & Investment Bank, you'll serve as a seasoned member of an agile team to deliver trusted market-leading technology products using AI/ML technologies in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives. You will need to leverage your strong knowledge of ML engineering, NLP, Python frameworks & libraries, LLM, and experience in working with massive amounts of data to build systems that reach JP Morgan scale.

Job Responsibilities

• Incorporate LLM models in business solutions.
• Build and enhance the AI processing pipeline to achieve higher throughput and accuracy by customizing for specific use cases by using tools like Langchain, few shot learning, Chain of thought and other prompt engineering techniques.
• Develop end-to-end ML pipelines necessary to transform existing applications and business processes into true AI systems.
• Implement Retrieval-Augmented Generation (RAG) methods to enhance the LLM's ability to retrieve and generate accurate answers from large datasets.
• Use Deep Learning frameworks like CNN, RNN, LSTM and Attention for solving use cases requiring semantic search, named entity resolution, forecasting, anomaly detection among many other techniques.
• Implement cloud-native solutions on AWS, ensuring high availability, scalability, and security and CI/CD integration.
• Utilize AI tech tools such as GitHub Copilot to enhance productivity and code quality.
• Participate in code reviews, providing constructive feedback to peers.

• Utilize Prompt Engineering techniques to fine-tune and optimize LLMs for specific use cases and improve response accuracy and relevance.

Required qualifications, capabilities and skills

• Formal training or certification on Applied AI ML Associate concepts and 2+ years applied experience
• Advanced Degree in field of Computer Science, Data Science or equivalent discipline.
• Working experience as a hands-on ML Engineer
• Strong hands on expertise with Python is a must have with experience in Python frameworks like Django, Flask or FastAPI. Experience with CI/CD pipelines, containerization (Docker, Kubernetes), and version control systems (Git).
• Experience working on document based GenAI use cases.
• Experience in building highly scalable distributed ML applications and MLOps experience. Good understanding of SQL is needed.
• Experience in AI Agents Frameworks, Langchain and LangGraph. Experience in Prompt Engineering & working in RAG solutions.
• Experience working with LLM & Vector embedding models. Experience with machine learning techniques and advanced analytics (e.g. regression, classification, clustering, time series, causal inference)

• Strong communication skills along with experience in taking requirements and working on them independently.

Preferred qualifications, capabilities and skills

• Experience as a ML Engineer, working on end to end stack is preferred.
• Experience in LLM, Prompt engineering, building RAG pipeline.
• Experience in the financial services industry or a similar regulated environment.
• Experience working with end-to-end pipelines consisting of Cloud services, MLOps is preferred. Experience with DevOps tools and practices.