D&T Lead - Data Science
Tasks
- Build ML CI/CD pipelines
- Build and optimize agentic AI workflows
- Deploy AI ML models and monitor performance
- Design end-to-end AI/ML solutions
- Establish MLOps practices for training deployment and monitoring
- Implement monitoring for model health drift and utilization
- Implement prompt design and context management
- Operate solutions on Google Cloud Platform
- Orchestrate data and ML workflows with Apache Airflow
- Train tune deploy and serve models on Vertex AI
- Translate business requirements into production solutions
- Use AlloyDB for data storage
- Use Cloud Batch for batch processing
- Use Cloud Run for serving
- Use Cloud SQL for relational storage
Perks/Benefits
- N/A
Skills/Tech-stack
Agentic AI | AlloyDB | Apache Airflow | Artificial Intelligence | CI/CD | Cloud Batch | Cloud Run | Cloud SQL | Cloud platform | Data Pipelines | Generative AI | Google Cloud | Google Cloud Platform | MLOps | Machine Learning | Model Monitoring | Python | Tokenomics | Vertex AI
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
Data Science | Data Science Lead | Engineer | Lead | Learning Engineer | Machine Learning Engineer | Science Lead
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