AI / Machine Learning Engineer
Tasks
- Build train evaluate predictive analytics and intelligent automation
- Deploy models into production environments
- Design develop deploy machine learning models
- Develop and maintain model-serving infrastructure
- Develop data pipelines and workflows for AI
- Document methodologies and technical solutions
- Ensure data quality and integrity
- Evaluate emerging machine learning frameworks and tools
- Evaluate model performance and implement continuous improvements
- Implement testing and validation for models
- Integrate machine learning with enterprise systems
- Monitor model performance and address drift
- Optimize data collection transformation and storage
- Perform feature engineering and data preparation
- Process and prepare large datasets
- Recommend improvements to AI architectures and development practices
- Stay current with AI and Machine Learning advancements
- Support model retraining and lifecycle management
- Support responsible AI and ethical AI practices
Perks/Benefits
Skills/Tech-stack
CI/CD | Cloud Computing | Computer Vision | Data Pipelines | Data Preprocessing | Data Quality | Deep learning | Distributed Computing | Docker | ETL | Feature Engineering | Kubernetes | MLOps | Machine Learning | Model Deployment | Model Evaluation | Model Optimization | Model Serving | NLP | Predictive Analytics | Python | Recommendation Systems | Statistical modeling | Supervised Learning | Unsupervised Learning | Version control
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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