Lead, Machine Learning Researcher
Tasks
- Collaborate with ML engineers and data engineers to productionize models
- Collect explore and prepare data
- Contribute to internal tools libraries and best practices
- Define interfaces and support product integration
- Design and run systematic experiments
- Develop and evaluate machine learning models
- Document methodology and findings
- Ensure fairness robustness and explainability
- Evaluate models using appropriate metrics
- Execute baselines and ablation studies
- Mentor peers through code reviews and internal talks
- Monitor model performance post-deployment
- Perform feature engineering and data cleaning
- Propose algorithms and model architectures
- Propose retraining and recalibration
- Run hyperparameter tuning
- Survey literature and state of the art techniques
- Translate business problems into machine learning research questions and success metrics
Perks/Benefits
- Career growth
- Collaborative team culture
- Flexible compensation and benefits package
- Professional development
Skills/Tech-stack
Ablation Studies | Data Preparation | Data cleaning | Experiment tracking | Explainability | Fairness | Feature Engineering | Hyperparameter Tuning | Language Processing | Machine Learning | Model Evaluation | Natural Language | Natural Language Processing | NumPy | Optimization | Pandas | PyTorch | Python | Recommender Systems | Robustness | SQL | Scikit-learn | Statistics | TensorFlow | Time Series
Education
Regions
Countries
States
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