Description

You will build, fine-tune, and deploy machine learning models into production environments.

This role is on-site.

Responsibilities

• Develop and fine-tune AI/ML models using PyTorch, TensorFlow, and Scikit-learn.
• Design data pipelines, perform feature engineering, and manage preprocessing for training and inference.
• Integrate models into business applications and APIs while ensuring scalability and performance.
• Collaborate with MLOps teams to deploy solutions using Docker, Kubernetes, and CI/CD pipelines on AWS, Azure, or Google Cloud.
• Conduct model evaluation, hyperparameter tuning, and implement continuous performance improvement strategies.

Required Skills

• 3-5 years of experience building and deploying AI/ML models into production.
• Proficiency in Python and PyTorch.
• Hands-on experience with Machine Learning and Artificial Intelligence.
• Experience setting up and managing CI/CD pipelines for model deployment.
• Practical knowledge of Docker and Kubernetes.
• Experience with cloud platforms including AWS or Azure.
• Proven ability to optimize models through data analysis and algorithm tuning.
• Background in model lifecycle management and production-grade AI systems.

Preferred Skills

• Experience with TensorFlow and Scikit-learn alongside PyTorch.
• Degree in M.E., MCA, BCA, B.E., or B.Tech.

Key Skills

Education

Any Graduate