Cognitive Linguist / Conversational AI Specialist

Veriipro; Chicago (IL); On-site; USD 110,000 - 170,000; Full time

Job summary

Veriipro is seeking a Cognitive Linguist / Conversational AI Specialist in Chicago to design, build, and maintain NLU models that identify end-user intent for a multichannel Virtual Assistant.

You will work with NLP, semantics, and intent modeling across multiple business domains to deliver accurate, engaging user experiences and iterate on models based on conversational data.

Qualifications

• Strong experience with NLP/NLU and conversational AI.
• Designing and maintaining NLU models and intent portfolios.
• Experience with training, evaluating, and tuning ML/NLU models.

Responsibilities

• Manage NLU intent portfolios across domains.
• Define intents, entities, training phrases, and flows.
• Analyze utterances to identify new intents and gaps.
• Build and continuously improve ML/NLU models for intent classification.
• Develop linguistic rules and training data for better recognition.
• Monitor and tune model performance over time.
• Collaborate with product owners, analysts, and engineers.
• Analyze conversations to improve accuracy and UX.
• Support maintenance of the Multichannel Virtual Assistant.

Skills

NLP/NLU expertise

Conversational AI

Intent classification

Entity recognition

Utterance modeling

Model training/evaluation

Multichannel platforms

Data-driven optimization

Collaboration with stakeholders

Job description

Job Summary

The Cognitive Linguist / Conversational AI Specialist will be responsible for designing, developing, and maintaining Natural Language Understanding (NLU) and machine learning models that identify end-user intent for a multichannel Virtual Assistant. The role requires strong expertise in conversational interfaces, NLP, intent modeling, and conversational AI, with a focus on delivering accurate and engaging user experiences across multiple business domains.

Required Technical / Functional Skills

• Strong experience with Natural Language Processing (NLP) and Natural Language Understanding (NLU).
• Experience designing and implementing conversational AI and Virtual Assistant solutions.
• Hands-on experience with intent classification, entity recognition, utterance modeling, and conversation flows.
• Experience building, training, evaluating, and maintaining machine learning/NLU models.
• Strong understanding of conversational interfaces and user interaction patterns.
• Experience working with multichannel conversational platforms.
• Ability to analyze conversational data and improve intent recognition and model performance.

Key Skills and Experience

• Experience working as a Cognitive Linguist, Conversational AI Specialist, NLP Specialist, or NLU Analyst.
• Strong understanding of linguistics, semantics, syntax, and conversational language patterns.
• Experience developing and maintaining intent portfolios across multiple business domains.
• Ability to create and optimize training utterances, intents, entities, and conversation models.
• Experience with NLU model testing, validation, tuning, and performance analysis.
• Familiarity with conversational analytics and identifying opportunities to improve Virtual Assistant performance.
• Experience collaborating with product owners, business analysts, developers, data scientists, and other technical stakeholders.

Roles and Responsibilities

• Understand and manage the NLU intent portfolio across multiple business domains, such as Technology, Human Resources, and other enterprise functions.
• Define, document, and maintain intents, entities, training phrases, and conversational flows.
• Analyze end-user utterances to identify new intents, variations, and potential gaps in the existing NLU model.
• Build, train, test, and continuously improve machine learning/NLU models for intent classification.
• Develop linguistic rules and training data to improve intent recognition and entity extraction.
• Monitor model performance and conduct regular tuning and optimization.
• Collaborate with business and technical teams to translate business requirements into conversational experiences.
• Perform conversation analysis and identify opportunities to improve accuracy, usability, and user experience.
• Support the ongoing maintenance and enhancement of the Virtual Assistant across multiple channels.
• Establish and maintain standards for NLU modeling, annotation, testing, and quality assurance.
• Document intent definitions, model changes, linguistic decisions, and testing results.