Description

You will design, develop, and deploy scalable AI/ML models and applications utilizing Large Language Models like OpenAI GPT.

This role is hybrid.

Responsibilities

• Build and maintain end-to-end MLOps pipelines covering data ingestion, chunking, vectorization, and model training.
• Deploy machine learning models into production environments using cloud platforms and containerization.
• Implement and optimize algorithms for classification, regression, clustering, and deep learning.
• Automate workflows using DevOps, MLOps, and LLMOps best practices, including CI/CD and automated retraining.
• Develop monitoring systems to track model performance and ensure optimal generalization.

Required Skills

• 5+ years of hands-on experience in AI/ML development and real-world model deployment.
• Expert proficiency in Python and libraries including TensorFlow, PyTorch, Keras, and Scikit-learn.
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Proficiency in containerization using Docker and Kubernetes.
• Strong understanding of deep learning, neural networks, NLP, and computer vision.
• Experience building CI/CD pipelines for machine learning workflows.
• Competency with data tools including Pandas, NumPy, and Matplotlib.
• Knowledge of SQL, NoSQL, and distributed computing frameworks like Spark.
• Experience with Git, Jupyter Notebooks, and CI/CD tools like Jenkins or CircleCI.

Key Skills

Education

Any Graduate