Data Scientist, AI & MLOps (mid-level) - Permanent
Tasks
- Build Docker container workflows
- Deploy train and maintain machine learning models
- Design, build, and validate machine learning models
- Establish KPIs and model improvement loops
- Implement CI/CD pipelines
- Maintain documentation version control and governance
- Prepare transform and optimize datasets in Snowflake
- Research integrate and apply emerging AI tools
- Set up model monitoring frameworks
- Translate business problems into measurable ML solutions
Perks/Benefits
Skills/Tech-stack
AWS | Airflow | Azure | Bitbucket | CI/CD | Cloud platform | DBT | Data pipeline | Docker | Feature Engineering | GDPR | Git | GitHub | Google Cloud | Google Cloud Platform | ISO | Kubernetes | Machine Learning | Model Governance | Model Monitoring | NumPy | Pandas | Power BI | PyTorch | Python | SQL | Scikit-learn | Snowflake | Stored Procedures | Tableau | TensorFlow
Education
N/A
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