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.

Disclaimer: This job posting and Location has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.