AIML Associate - DCL

JPMorganChase • Jersey City, NJ

2d

About The Position

As a AI/ML Engineer at JPMorgan Chase within the Corporate Oversight and Governance Technology AI/ML team, you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products 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. Job responsibilities Work closely with product managers, data scientists, ML engineers, and other stakeholders to understand requirements and prioritize use cases. Design, develop, and deploy state-of-the-art AI/ML/LLM/GenAI solutions to meet business objectives. Develop and maintain automated pipelines for model deployment, ensuring scalability, reliability, and efficiency. Implement optimization strategies to fine-tune generative models for specific GenAI use cases, ensuring high-quality outputs in summarization and text generation. Conduct thorough evaluations of generative models (e.g., GPT-5.2), iterate on model architectures, and implement improvements to enhance overall performance in LLM applications. Implement monitoring mechanisms to track model performance in real-time and ensure model reliability. Communicate AI/ML/LLM/GenAI capabilities and results to both technical and non-technical audiences. Stay informed about the latest trends and advancements in the latest AI/ML/LLM/GenAI research, implement cutting-edge techniques, and leverage external APIs for enhanced functionality.

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field
• 3+ years of demonstrated experience in applied AI/ML engineering, with a track record of developing and deploying business critical machine learning models in production.
• Proficiency in programming languages like Python for model development, experimentation, and integration with OpenAI API.
• Experience with machine learning frameworks, libraries, and APIs, such as TensorFlow, PyTorch, Scikit-learn, and OpenAI API.
• Experience with cloud computing platforms (e.g., AWS, Azure, or Google Cloud Platform), containerization technologies (e.g., Docker and Kubernetes), and microservices design, implementation, and performance optimization.
• Solid understanding of fundamentals of statistics, machine learning (e.g., classification, regression, time series, deep learning, reinforcement learning), and generative model architectures, particularly Transformer.
• Ability to identify and address AI/ML/LLM/GenAI challenges, implement optimizations and fine-tune models for optimal performance in NLP applications.
• Strong collaboration skills to work effectively with cross-functional teams, communicate complex concepts, and contribute to interdisciplinary projects.
• A portfolio showcasing successful applications of generative models in LLM projects, including examples of utilizing OpenAI APIs and model fine-tuning.

Nice To Haves

• Familiarity with the financial services industries.
• Expertise in designing and implementing pipelines using Retrieval-Augmented Generation (RAG) and Agentic AI framework
• Hands-on knowledge of Chain-of-Thoughts, Tree-of-Thoughts, Graph-of-Thoughts prompting strategies.

Responsibilities

• Work closely with product managers, data scientists, ML engineers, and other stakeholders to understand requirements and prioritize use cases.
• Design, develop, and deploy state-of-the-art AI/ML/LLM/GenAI solutions to meet business objectives.
• Develop and maintain automated pipelines for model deployment, ensuring scalability, reliability, and efficiency.
• Implement optimization strategies to fine-tune generative models for specific GenAI use cases, ensuring high-quality outputs in summarization and text generation.
• Conduct thorough evaluations of generative models (e.g., GPT-5.2), iterate on model architectures, and implement improvements to enhance overall performance in LLM applications.
• Implement monitoring mechanisms to track model performance in real-time and ensure model reliability.
• Communicate AI/ML/LLM/GenAI capabilities and results to both technical and non-technical audiences.
• Stay informed about the latest trends and advancements in the latest AI/ML/LLM/GenAI research, implement cutting-edge techniques, and leverage external APIs for enhanced functionality.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level