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Machine Learning Engineer
2 weeks ago
Key Responsibilities:
Machine Learning Development:
- Design and implement ML models for predictive analytics, classification, regression, and clustering.
- Perform feature engineering, model tuning, and validation using frameworks like scikit-learn, TensorFlow, or PyTorch.
- Deploy ML models into production environments and monitor performance.
Data Engineering & Processing:
- Build and optimize large-scale data pipelines using PySpark for distributed processing.
- Handle structured and unstructured data from multiple sources.
- Ensure data quality, consistency, and security across workflows.
Programming & Automation:
- Develop reusable scripts and automation tools in Python for data ingestion, transformation, and ML workflows.
- Implement best practices for code quality, testing, and version control (Git).
Collaboration & Integration:
- Work closely with data scientists, analysts, and business teams to translate requirements into technical solutions.
- Integrate ML models with APIs and applications for real-time predictions.
Required Skills:
- Strong proficiency in Python and ML libraries (scikit-learn, TensorFlow, PyTorch).
- Hands-on experience with PySpark for big data processing.
- Solid understanding of ML concepts: supervised/unsupervised learning, model evaluation, hyperparameter tuning.
- Knowledge of SQL/NoSQL databases and data warehousing.
- Familiarity with cloud platforms (AWS, Azure, GCP) and MLOps practices.
