Technical Trainer AI ML (Part time / Training Partner)

Job highlights

• Capstone Project: Handle and mentor Capstone projects for students. Offline Delivery : Offline training delivery to be done in partner colleges
• AI ML : Experience in teaching,training and mentoring
• . Offline training to be conducted in partner colleges
• Required for its robust libraries (e.g.,

Key Responsibilities

• Model Development: Design, train, and fine-tune machine learning and deep learning models to solve specific business problems.
• Capstone Project: Handle and mentor Capstone projects for students
• Offline Delivery : Offline training delivery to be done in partner colleges.
• Data Pipelines: Construct, optimize, and maintain data pipelines to collect, clean, and feed raw data into models.
• Deployment MLOps: Integrate models into production environments and ensure they run efficiently at scale.
• Evaluation: Conduct experiments, A/B testing, and monitor model performance (accuracy, latency, and scalability) post-deployment
• AI ML : Experience in teaching, training and mentoring
• Python: The undisputed industry standard. Required for its robust libraries (e.g., PyTorch , TensorFlow , Scikit-Learn) and data handling.
• SQL: Essential for querying relational databases and preparing training data.
• Java Scala: Often utilized for large-scale enterprise data processing pipelines (like Apache Spark).
• C++ / Julia: Occasionally required for roles focused on intense computational performance, research, and deep learning simulation

PyTorch Foundation

PyTorch Foundation is the deep learning community home for the open source PyTorch framework and ecosystem.

Offline training to be conducted in partner colleges.

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