AI Engineer 2
Tasks
- Apply MLOps best practices for version control testing documentation and deployment automation
- Build data preparation and feature engineering pipelines
- Collaborate with data engineers software engineers and product teams
- Create and manage datasets for training validation and evaluation
- Develop and support AI and machine learning models
- Implement and optimize machine learning workflows and model serving
- Integrate AI models into applications and APIs
- Perform code reviews and knowledge sharing
- Test validate monitor and analyze model performance
- Troubleshoot model performance data quality and system functionality
Perks/Benefits
- N/A
Skills/Tech-stack
APIs | AWS | Azure | CI/CD | Cloud platform | Deep learning | Embeddings | Feature Engineering | Generative AI | Google Cloud | Google Cloud Platform | Language Models | Large Language Models | MLOps | Machine Learning | Model Evaluation | Model Monitoring | Model Training | PyTorch | Python | TensorFlow | Testing | Tokenization | Transformer Architecture | Version control
Roles
AI | AI Engineer | Engineer
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