Computational Linguist - Machine Learning and Optimization Team - Sr. Associate

Join our Machine Learning and Optimization team to shape the future of conversational AI at Chase.

You'll help transform customer interactions by leveraging advanced LLMs and cutting-edge NLP techniques.

This is an opportunity to grow your career, collaborate with experts, and make a real impact on our digital products.

As a Computational Linguist in the Machine Learning and Optimization team, you will optimize features, models, and AI capabilities for the Chase Digital Assistant and other conversational AI products.

You will drive the transition to LLM-based, context-rich conversational AI, develop scalable intent taxonomies, and refine conversation flows.

You will work closely with cross-functional teams to deliver high-quality models and innovative solutions, ensuring scalability and resiliency.

You will collaborate with annotation leads, product managers, and ML engineers to enhance training data and conversational flows.

Your expertise will support continuous improvement in customer experience and journey design, while maintaining documentation and best practices for Natural Language Understanding processes.

Job Responsibilities


* Manage, monitor, and evaluate the Chase Digital Assistant's intent and entity taxonomy and the model training.


* Collaborate with developers, machine learning engineers, and quality assurance teams to resolve model-related issues as they occur.


* Serve as a subject matter expert, engaging with various stakeholders throughout the product lifecycle, and maintain a strong understanding of the Chase Digital Assistant's model from both customer and technical perspectives.


* Work closely on the adaptation to LLM-driven workflows, ensuring seamless integration of LLMs with existing conversational AI architectures and event tracking systems.


* Work closely with Product Managers, ML Engineers, and Analytics by providing linguistic expertise and direction for new NLP capabilities (e.g., dialogue, ambiguity, inference).


* Design, evaluate, and optimize prompts and intent/flow descriptions for LLM-powered chatbots, ensuring more intelligent dialogue management and generative repair capabilities.


* Partners closely with Annotation Lead to review and optimize training data, including large-scale refreshes and revisions of training sets and intent/flow/slot descriptions.


* As a subject matter expert, be a resource for the annotation team for their understanding and evaluation of customer language and the models.


* Collaborate on the transition from single-utterance, manual analysis to full-conversation, structured context analysis, leveraging LLMs for nuanced understanding and targeted optimization.


* Implement and monitor performance metrics (e.g., F1 Score), report results to identify gaps and performance optimization opportunities.


* Implement current metrics to assess LLM-powered chatbot performance, and strengthen the evaluation process by introducing new metrics t...