Machine Learning Engineer
Tasks
- Build attribution and regression models
- Build tools to apply analytics models
- Conduct causality analysis
- Conduct large scale analysis to discover patterns and trends
- Design and develop machine learning models
- Develop deep learning models
- Extend machine learning frameworks and AI frameworks
- Perform statistical analysis and interpret results
- Perform topological data modeling
- Perform variable importance analysis
- Run machine learning tests and experiments
- Train and retrain systems to prevent drift
- Transform structured data into insights
Perks/Benefits
- Accident insurance
- Health insurance
- Hybrid work
- Life insurance
- Retirement savings plans
- Training and coaching
- Tuition reimbursement
Skills/Tech-stack
AWS | Attribution Modeling | Autoencoders | Azure | CI/CD | Causality | Data Analysis | Forecasting | GCP | Generative AI | Graph Modeling | Hypergraph | Keras | Langchain | Network Analysis | Neural Networks | PyTorch | Python | Regression | Reinforcement Learning | SQL | Scikit-learn | Supervised Learning | TensorFlow | Topological Data | Topological Data Analysis | Unsupervised Learning | Variable Importance | XGBoost
Education
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