Conversational Analytics Engineer - GCP
Tasks
- Apply MLOps best practices for production deployments
- Build and integrate analytical agents into applications
- Collaborate with engineering, product, and business teams
- Communicate technical concepts to non-technical stakeholders
- Define assess data quality and timeliness
- Design scalable data solutions
- Develop deploy machine learning and artificial intelligence solutions
- Implement evaluation frameworks for model performance
- Lead client conversations to shape data and analytics solutions
- Orchestrate APIs for integration between models data pipelines and applications
- Power conversational and analytical use cases using Gemini
- Translate business challenges into data and AI solutions
Perks/Benefits
- Career advancement
- Hybrid work option
- Learning and development training access
- Professional development programs
- Remote work option
Skills/Tech-stack
API Orchestration | Agentic AI | Artificial Intelligence | BigQuery | Cloud platform | Embeddings | Evaluation | Git | Google Cloud | Google Cloud Platform | Language Models | Large Language Models | MLOps | Machine Learning | Python | Retrieval-Augmented Generation | SQL
Education
N/A
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