Senior AI Engineer
Tasks
- Build and maintain reusable AI frameworks and best practices
- Design and implement AI ML solutions on Databricks
- Diagnose and resolve issues across data pipelines and ML workflows
- Drive adoption of MLOps including CI CD model monitoring governance and lifecycle management
- Optimize Databricks workflows and advance platform capabilities
- Provide technical guidance for model development and deployment
- Support and enhance Databricks platform performance reliability and cost efficiency
- Translate business problems into scalable AI architectures
Perks/Benefits
- Defined benefit pension
- Extra vacation days
- Flexible work schedule
- Health dental disability and life insurance
- Hybrid work model
- Relocation assistance
Skills/Tech-stack
AWS | Apache Spark | CI/CD | Cloud platform | Data Engineering | Data Pipelines | Data Processing | Databricks | Delta Lake | Distributed data | Distributed data processing | GitHub | Google Cloud | Google Cloud Platform | Langchain | MLOps | MLflow | Machine Learning | Microsoft Azure | Model Monitoring | Model versioning | PySpark | PyTorch | Python | Retrieval-Augmented Generation | Scikit-learn | TensorFlow | Unity Catalog | Vector Databases
Roles
AI Engineer | Developer | Engineer | Senior AI Engineer | Senior Developer
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