Key Responsibilities
- Develop and deploy end-to-end machine learning models for regression, classification, and clustering tasks
- Perform data preprocessing, feature engineering, and statistical analysis to derive actionable insights
- Design and optimize ML pipelines for training, validation, and deployment
- Evaluate and tune model performance using advanced techniques
- Collaborate with cross-functional teams to integrate ML solutions into production systems
- Monitor and maintain deployed models for accuracy and scalability
Requirements
- Strong expertise in Python with hands-on experience in NumPy, Pandas, and Scikit-learn
- Proven experience building and deploying ML models using TensorFlow or PyTorch
- Deep knowledge of statistics, probability, and ML algorithms
- Proficiency in SQL and working with large datasets
- Familiarity with cloud platforms (AWS, Azure, or GCP) and ML model deployment (APIs, batch, real-time)
- Experience in at least one domain: NLP, Time Series, or Recommendation Systems