Jobs in Dana Point, CA
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GenAI Architect & Data Scientist
Salary not disclosed
Title: GenAI Architect & Data Scientist 100% Remote Description: We are seeking a GenAI Architect & Data Scientist to design and build intelligent, scalable AI systems with a strong focus on Natural Language Processing (NLP) and Generative AIdriven conversational experiences.
The ideal candidate will combine deep data science expertise with architectural thinking to deliver intent-driven, context-aware, and production-ready AI solutions across cloud platforms.
This role requires 12+ years of hands-on and architectural experience in large-scale enterprise environments.
Key Responsibilities GenAI & NLP Solution Design Design and architect Generative AI solutions leveraging Large Language Models (LLMs).
Build and optimize NLP pipelines for intent detection, entity extraction, sentiment analysis, summarization, and conversational understanding.
Apply generative AI techniques to automate and enhance complex language-based interactions.
Design scalable AI architectures supporting multi-channel conversational platforms (web, chat, voice, APIs).
Intent Design & Conversational AI Analyze user behavior and business requirements to define intent hierarchies.
Design dialogue flows, fallback strategies, and contextual conversation handling.
Improve conversational accuracy using prompt engineering, fine-tuning, and Retrieval-Augmented Generation (RAG).
Ensure conversational experiences align with business goals and are explainable.
Data Science & Model Development Develop, train, evaluate, and optimize ML and deep learning models for NLP use cases.
Work with structured and unstructured data.
Perform feature engineering, experimentation, and model validation.
MLOps & Production Readiness Implement MLOps pipelines for model versioning, deployment, monitoring, and retraining.
Ensure production readiness with observability, performance tracking, and governance controls.
Collaborate with DevOps teams for enterprise AI integration.
Cloud AI & Architecture Design and deploy AI solutions on AWS, Azure, or GCP.
Leverage managed AI/ML services for training and inference.
Ensure scalability, security, compliance, and cost optimization.
Collaboration & Leadership Collaborate with product managers, engineers, UX designers, and stakeholders.
Provide architectural guidance and technical leadership.
Mentor data scientists and engineers on GenAI and MLOps best practices.
Required Skills Core Technical Skills Strong expertise in Natural Language Processing (NLP).
Hands-on experience with Generative AI and Large Language Models (LLMs).
Proven experience in Intent Design and conversational AI systems.
Strong background in Data Science and Machine Learning.
Experience implementing MLOps frameworks.
The ideal candidate will combine deep data science expertise with architectural thinking to deliver intent-driven, context-aware, and production-ready AI solutions across cloud platforms.
This role requires 12+ years of hands-on and architectural experience in large-scale enterprise environments.
Key Responsibilities GenAI & NLP Solution Design Design and architect Generative AI solutions leveraging Large Language Models (LLMs).
Build and optimize NLP pipelines for intent detection, entity extraction, sentiment analysis, summarization, and conversational understanding.
Apply generative AI techniques to automate and enhance complex language-based interactions.
Design scalable AI architectures supporting multi-channel conversational platforms (web, chat, voice, APIs).
Intent Design & Conversational AI Analyze user behavior and business requirements to define intent hierarchies.
Design dialogue flows, fallback strategies, and contextual conversation handling.
Improve conversational accuracy using prompt engineering, fine-tuning, and Retrieval-Augmented Generation (RAG).
Ensure conversational experiences align with business goals and are explainable.
Data Science & Model Development Develop, train, evaluate, and optimize ML and deep learning models for NLP use cases.
Work with structured and unstructured data.
Perform feature engineering, experimentation, and model validation.
MLOps & Production Readiness Implement MLOps pipelines for model versioning, deployment, monitoring, and retraining.
Ensure production readiness with observability, performance tracking, and governance controls.
Collaborate with DevOps teams for enterprise AI integration.
Cloud AI & Architecture Design and deploy AI solutions on AWS, Azure, or GCP.
Leverage managed AI/ML services for training and inference.
Ensure scalability, security, compliance, and cost optimization.
Collaboration & Leadership Collaborate with product managers, engineers, UX designers, and stakeholders.
Provide architectural guidance and technical leadership.
Mentor data scientists and engineers on GenAI and MLOps best practices.
Required Skills Core Technical Skills Strong expertise in Natural Language Processing (NLP).
Hands-on experience with Generative AI and Large Language Models (LLMs).
Proven experience in Intent Design and conversational AI systems.
Strong background in Data Science and Machine Learning.
Experience implementing MLOps frameworks.
Not Specified
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