Applied AI ML [Multiple Positions Available]
Tasks
- Build and train production machine learning models
- Build batch and real-time prediction pipelines
- Build deep learning and generative AI solutions
- Communicate ml results to non technical audiences
- Conduct data analysis and proof of concept modeling
- Create data pipelines for model deployment and operationalization
- Deploy distributed machine learning models in production
- Develop end to end ml pipelines for ai transformation
- Engineer features using large scale data processing
- Implement mlops for model monitoring and automated retraining
- Monitor model performance and support operational analytics
- Perform data quality validation and enrichment
- Perform hyperparameter tuning and model selection
Perks/Benefits
- Backup childcare
- Financial coaching
- Health care
- Mental health support
- On-site health and wellness centers
- Retirement savings plan
- Tuition reimbursement
Skills/Tech-stack
Anomaly Detection | Automated retraining | CI/CD | Classification | Cloud Computing | Clustering | Containerization | Data Enrichment | Data Quality | Data cleaning | Deep learning | Dimensionality Reduction | Docker | Entity Extraction | Feature Engineering | Generative AI | Hyperparameter Tuning | Kubernetes | Language Processing | MLOps | Machine Learning | Model Evaluation | Model Monitoring | Model selection | Natural Language | Natural Language Processing | PySpark | Python | RESTful API | Regression | SQL | Sentiment Analysis | Series analysis | Time Series | Time Series Analysis | Version control
Regions
Countries
States
Cities
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