AI / Machine Learning Engineer
Tasks
- Build model serving infrastructure
- Deploy models to production
- Design machine learning models
- Develop data pipelines
- Develop predictive analytics
- Document technical solutions
- Ensure data quality and integrity
- Ensure model governance compliance
- Evaluate model performance
- Evaluate new machine learning frameworks
- Handle model drift
- Implement testing and validation
- Integrate machine learning with enterprise systems
- Monitor model performance
- Optimize data collection transformation storage
- Perform feature engineering
- Prepare data for modeling
- Recommend AI architecture improvements
- Research machine learning advancements
- Support model retraining
- Train machine learning models
Perks/Benefits
- N/A
Skills/Tech-stack
CI/CD | Cloud Computing | Computer Vision | Data Governance | Data Pipelines | Data Preprocessing | Data Quality | Deep learning | Distributed Computing | Docker | ETL | Feature Engineering | Kubernetes | Language Processing | MLOps | Machine Learning | Model Deployment | Model Evaluation | Model Monitoring | Model Serving | Model retraining | Natural Language | Natural Language Processing | Predictive Analytics | PyTorch | Python | Recommendation Systems | Scikit-learn | Security Compliance | Statistical modeling | Supervised Learning | TensorFlow | Testing | Unsupervised Learning | Version control | XGBoost
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
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