Google Cloud ML Engineer
- Architect, design, and develop scalable chat Virtual Agent frameworks using Google Vertex AI (Agent Engine, ADK).
- Build, customize, and optimize chatbots and conversational flows with Dialogflow CX/ES (intent detection, context management, slot filling, rich fulfillment).
- Apply NLP, LLM, and GenAI models on Vertex AI for advanced chatbot capabilities (summarization, entity extraction, response generation).
- Develop and maintain cloud-native chat Virtual Agent solutions using GCP services (CCAI, Pub/Sub, Cloud Functions, Cloud Run, Cloud Storage, BigQuery).
- Train, fine-tune, and deploy custom LLMs, transformer models, and RAG pipelines .
- Implement MLOps best practices (Vertex AI Pipelines, Docker, Kubernetes, CI/CD workflows).
- Develop REST APIs, gRPC, and JSON-based integrations for seamless system communication.
Required Qualifications
- 6+ years in software development (4+ years in NLP/NLU for chat).
- Advanced Python skills with ML/NLP libraries (Hugging Face, TensorFlow, PyTorch).
- Proven success building conversational agents with Vertex AI and Dialogflow CX/ES .
- Proficiency in GCP services and cloud-native architectures.
- Strong MLOps knowledge (Docker, Kubernetes, CI/CD, Git).
- Experience with Agent Assist functionality is a plus.
Preferred Qualifications
- Master’s/PhD in Computer Science, AI/ML, or related field.
- GCP certifications (e.g., Google Cloud Certified Professional ML Engineer).
- Experience with GenAI frameworks (PaLM, Gemini).
- Integration with CRM, knowledge bases, and live agent systems.
- Knowledge of security and compliance in conversational AI.
Soft Skills
- Excellent communication and collaboration.
- Strong ownership and end-to-end project delivery.
- Leadership in cross-functional environments.
- Team leading and management skills.
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