Description

You will lead the end-to-end machine learning lifecycle, from model selection to production deployment.

Responsibilities

• Propose and select appropriate AI/ML models including regression, classification, clustering, and deep learning.
• Curate, clean, and preprocess raw data to ensure high data quality.
• Perform feature engineering to improve model performance.
• Train and optimize models through hyperparameter tuning using grid search or random search.
• Evaluate model performance using metrics such as accuracy, precision, recall, and F1 score.
• Deploy models into production environments using Docker or cloud platforms like AWS and Azure.

Required Skills

• 5+ years of experience in data science or machine learning roles.
• Proficiency in Python, R, or Java.
• Strong SQL skills for data extraction and manipulation.
• Experience with data manipulation libraries such as Pandas and NumPy.
• Competency in data visualization tools like Matplotlib and Seaborn.
• Deep understanding of statistical concepts and machine learning algorithms.
• Experience with model deployment via Docker or cloud platforms (AWS/Azure).
• Ability to communicate complex technical concepts to non-technical stakeholders.
• Proven ability to manage projects, prioritize tasks, and meet deadlines.

Key Skills

Education

Any Graduate