AIML Associate - DCL

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.

Required qualifications, capabilities, and skills


* 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 appli...