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Google Cloud ML Engineer at Cloud Analytics Technologies LLC Dallas, TX

Job in Dallas, Dallas County, Texas, 75215, USA
Listing for: Itlearn360
Full Time position
Listed on 2026-01-17
Job specializations:
  • IT/Tech
    AI Engineer, Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 80000 - 100000 USD Yearly USD 80000.00 100000.00 YEAR
Job Description & How to Apply Below

Google Cloud ML Engineer job at Cloud Analytics Technologies LLC. Dallas, TX.

  • 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, Big Query).
  • 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, Tensor Flow, 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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