Senior Data Scientist / AI Machine Learning Research Engineer
Tasks
- Apply statistics linear algebra calculus
- Build CI CD pipelines for model deployment
- Build data pipelines with ETL
- Deploy machine learning models on cloud
- Design data warehousing solutions
- Develop machine learning algorithms
- Ensure reproducible research
- Establish machine learning governance
- Implement containerization and orchestration
- Implement dataset and model version control
- Monitor deployed models
- Optimize large scale data processing workflows
- Track machine learning experiments
- Train models with PyTorch
- Train models with TensorFlow
- Train models with scikit learn
- Use Airflow for workflow orchestration
- Use Python for machine learning development
- Use SQL for data querying
- Use Spark for data engineering
Perks/Benefits
Skills/Tech-stack
AWS | Apache Airflow | Apache Spark | Azure | CI/CD | Calculus | Cloud infrastructure | Cloud platform | Computer Networking | Containerization | Data Pipelines | Data Warehousing | ETL | Experiment tracking | Google Cloud | Google Cloud Platform | Kubernetes | Linear Algebra | Linux | Machine Learning | Model Monitoring | PyTorch | Python | RF domain | Reproducible Research | SQL | Scikit-learn | Series analysis | Signal Processing | Statistics | TensorFlow | Time Series | Time Series Analysis | Version control
Education
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