Description

You will design, build, and optimize machine learning models for production environments, focusing on scalability and performance.

This role is on-site.

Responsibilities

• Translate business requirements into technical machine learning solutions.
• Develop and deploy scalable ML models within production environments.
• Implement MLOps pipelines covering data ingestion, feature engineering, training, deployment, and monitoring.
• Evaluate and improve model performance to address drift and degradation.
• Conduct code reviews and contribute to technical knowledge sharing within the team.

Required Skills

• 5+ years of experience with Python programming.
• Proficiency with TensorFlow and PyTorch.
• Experience using AWS or Azure cloud platforms.
• Hands-on experience with NumPy, Pandas, and Scikit-learn.
• Knowledge of ML algorithms including linear/logistic regression, decision trees, random forests, and SVMs.
• Experience with deep learning architectures such as CNNs, RNNs, and transformers.
• Competency in data preprocessing, feature engineering, and hyperparameter tuning.
• Solid foundation in probability and statistics, including hypothesis testing and Bayesian inference.

Preferred Skills

• BE or BTech in Computer Science Engineering or a related discipline.
• Postgraduate degrees (MTech or MS) in relevant fields.

Key Skills

Education

Any Graduate