Google Cloud AI & Data Science Engineer (Dialogflow, Vertex AI, & Multimodal AI)

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Requirements:

• 3+ years of hands-on experience with Dialogflow CX, including complex conversation flows, fulfillment, and webhook integrations.
• Strong expertise in Vertex AI (model training, fine-tuning, LLMs, embedding techniques, and API usage).
• Experience in data science, statistical modeling, and machine learning frameworks like TensorFlow, PyTorch, or Scikit-learn.
• Solid experience with Google Cloud Platform (GCP) services such as Cloud Functions, Cloud Run, Pub/Sub, and BigQuery.
• Experience designing production-ready AI services, including API gateways, databases, job batching, and cloud-based workflows.
• Proficiency in Python or Node.js for AI integration, data processing, and backend development.
• Expertise in handling large unstructured datasets, including natural language processing (NLP), computer vision, and deep learning.
• Understanding of AI ethics, bias reduction, and responsible AI deployment.
• Experience working with RESTful APIs, GraphQL, and third-party AI integrations.
• Knowledge of multimodal AI (text, speech, image, and video processing) within Google AI systems.
• Strong problem-solving skills, with the ability to optimize AI models for performance and scalability.

Responsibilities:

• Develop & Optimize AI Agents: Design and implement AI-driven conversational experiences using Dialogflow CX, integrating with Vertex AI for advanced NLP, LLM capabilities, and multimodal interactions.
• Custom AI Model Training & Data Science: Develop and train custom AI models using structured and unstructured data, leveraging Vertex AI, TensorFlow, PyTorch, and AutoML.
• Data Processing & Analysis: Work with large-scale datasets, performing data preprocessing, feature engineering, and AI-driven insights generation.
• Cloud Architecture & Deployment: Architect scalable AI solutions within Google Cloud Platform (GCP), ensuring high availability, performance, and cost efficiency.
• Production-Ready AI Services: Design and deploy scalable and efficient AI services, including setting up API gateways, databases, job batching systems, and cloud-based service layers.
• Multimodal AI Capabilities: Build AI solutions that process text, speech, image, and video data, integrating APIs and Google’s AI agent ecosystem.
• AI-Driven Insights & Predictive Analytics: Apply machine learning techniques for predictive analytics, recommendation systems, and anomaly detection.
• API Development & Integration: Develop backend services and APIs to integrate AI models with customer applications, ensuring seamless data flow.
• Infrastructure & Resource Management: Set up and maintain serverless and containerized deployments, including Cloud Run, Kubernetes, and managed database solutions.
• Testing & Validation: Implement automated testing, model validation, and AI evaluation frameworks to ensure accuracy and responsiveness.
• Security & Compliance: Ensure AI models comply with data privacy regulations (GDPR, HIPAA, etc.) and industry best practices.
• Collaboration & Documentation: Work closely with product managers, developers, and stakeholders to align AI implementations with business objectives. Maintain detailed documentation of AI workflows, architectures, and model training processes.