AI/ML Engineer - Agentic AI & Vertex AI
Tasks
- Architect scalable agentic AI solutions
- Build and optimize real-time and batch data pipelines
- Build and orchestrate multi-agent systems
- Design and develop intelligent AI agents
- Enable low latency inference with Vertex AI Endpoints
- Implement retrieval augmented architectures with vector search
- Integrate Model Context Protocol Toolbox with enterprise data platforms
- Integrate with BigQuery for feature engineering and analytics
- Train fine tune evaluate and deploy Vertex AI models
Perks/Benefits
- Company-Paid Holidays
- Disability insurance
- Employee assistance program
- Life insurance
- Medical, dental, and vision coverage
- Paid time off
- Personal days
- Retirement savings plan
- Sick leave
Skills/Tech-stack
AI Agent Builder | AI Model Garden | AI Pipelines | AI endpoints | Agent Builder | Agent Development | Agent Development Kit | Agent Development Kit ADK | Agent systems | AlloyDB | BigQuery | Cloud Spanner | Cloud Storage | Cloud platform | Data Normalization | Data Preprocessing | Data encoding | Data masking | Data redaction | Dataflow | Feature Engineering | Google Cloud | Google Cloud Platform | Google Cloud Storage | MCP Toolbox | Missing Value Imputation | Model Context Protocol | Model Context Protocol MCP | Model Evaluation | Model Garden | Model Performance Monitoring | Model performance | Multi-Agent | Multi-Agent Systems | Performance Monitoring | Protocol MCP | Python | Retrieval-Augmented Generation | RunInference APIs | SQL | Vector Search | Vertex AI | Vertex AI Agent Builder | Vertex AI Endpoints | Vertex AI Model Garden | Vertex AI pipelines
Education
N/A
Roles
AI | AI/ML Engineer | Engineer | Learning Engineer | ML Engineer | Machine Learning Engineer
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