Transformative AI/ML Engineer

6 days ago

kanpur, India beBeeAI Full time

Reimagining Customer Engagement in HealthcareWe're revolutionizing the way patients interact with their healthcare providers by combining cutting-edge technology with advanced AI capabilities. Our innovative approach is transforming the primary care experience from end-to-end.Developing AI Models: Lead the design and implementation of Large Language Model (LLM) and Retrieval-Augmented Generation (RAG) systems to ingest data sources, generate accurate responses, and power chatbot and voice agent interactions.Prompt Engineering & Voice Agent Design: Craft, iterate and optimize prompts and voice-agent dialogue flows to maximize response relevance, reduce latency, and ensure clinical safety across text and voice channels.Cross-Functional Collaboration: Partner with frontend and backend teams to integrate AI and voice agent components into a microservices architecture.Performance Monitoring & Optimisation: Instrument AI pipelines, analyze logs and user feedback, troubleshoot edge cases, and implement continuous-learning improvements.Innovation & R&D: Stay up-to-date with the latest advances in LLMs, RAG, conversational AI frameworks, and NHS-specific compliance to inform our technical roadmap.Testing & Validation: Define and execute rigorous test plans in collaboration with QA to validate model accuracy, voice-agent performance, and compliance with healthcare standards.Technical Leadership: Mentor junior engineers, advocate for best practices in MLOps, prompt engineering, voice-agent design, and model governance, and contribute to architecture reviews.About This RoleThis is an exceptional opportunity to join our team as a skilled AI/ML Engineer who can drive innovation and excellence in customer engagement solutions. If you're passionate about harnessing AI capabilities to transform healthcare experiences, we'd love to hear from you.Key ResponsibilitiesArchitect & Deploy AI Models: Develop and deploy LLM- and RAG-based systems to ingest data sources, generate accurate responses, and power chatbot and voice agent interactions.Prompt & Voice Agent Engineering: Craft, iterate and optimize prompts and voice-agent dialogue flows to maximize response relevance, reduce latency, and ensure clinical safety across text and voice channels.Cross-Functional Collaboration: Partner with frontend and backend teams to integrate AI and voice agent components into a microservices architecture.Performance Monitoring & Optimisation: Instrument AI pipelines, analyze logs and user feedback, troubleshoot edge cases, and implement continuous-learning improvements.Innovation & R&D: Stay up-to-date with the latest advances in LLMs, RAG, conversational AI frameworks, and NHS-specific compliance to inform our technical roadmap.Testing & Validation: Define and execute rigorous test plans in collaboration with QA to validate model accuracy, voice-agent performance, and compliance with healthcare standards.Technical Leadership: Mentor junior engineers, advocate for best practices in MLOps, prompt engineering, voice-agent design, and model governance, and contribute to architecture reviews.

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