AI/ML Part-Trainer(offline)

3 - 5 years

0 Lacs

Posted:2 weeks ago| Platform: Foundit logo

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Work Mode

On-site

Job Type

Full Time

Job Description

Job Overview

CliniLaunch Research Institute is seeking askilled and passionate Part-Time AI/ML Trainerto conductoffline classroom sessionsfor students and professionals aspiring to build a career inArtificial Intelligence and Machine Learning.

The ideal candidate should have strong industry experience, the ability to simplify complex AI/ML concepts, and a passion for teaching and mentoring learners to achieve professional excellence.

Key Responsibilities

  • Conductoffline (in-person)classroom training sessions on:
  • Machine Learning Algorithms
  • Deep Learning
  • Natural Language Processing (NLP)
  • Computer Vision
  • Model Evaluation & Deployment
  • Python for Data Science
  • Guide students through practical, hands-on projects usingPython, TensorFlow, PyTorch, Scikit-learn, and Jupyter Notebooks.
  • Support students in preparing for recognized certifications (e.g.,TensorFlow Developer,AWS Certified Machine Learning).
  • Evaluate learner performance and provide personalized feedback.
  • Collaborate with the academic team to improve course content and delivery.
  • Stay updated withAI/ML advancementsand integrate new tools and technologies into training.

Required Qualifications

  • 35 years of professional experience inAI, Machine Learning, or Data Science.
  • Proven experience as atrainer, mentor, or instructorin AI/ML.
  • Strong proficiency inPythonand ML libraries (TensorFlow, PyTorch, Scikit-learn, etc.).
  • Excellent communication and presentation skills.
  • Experience withcloud-based ML platforms (AWS, Azure, or GCP)is an advantage.

Preferred Certifications

  • TensorFlow Developer Certificate
  • AWS Certified Machine Learning Specialty
  • Microsoft Certified: Azure AI Engineer Associate
  • IBM AI Engineering Professional Certificate
  • Google Cloud Professional Machine Learning Engineer

Key Skills & Attributes

  • Strong foundation insupervised/unsupervised learning, deep learning, and model optimization.
  • Ability to engage students and simplify complex technical concepts.
  • Passion for mentoring and guiding aspiring professionals.
  • Excellent organizational and time management skills for part-time classroom sessions.

Compensation

  • Based on thenumber of batches delivered

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