AI/ML Trainer

2 days ago


Pune, India Futurism Technologies, INC. Full time

Job Title: AI/ML TrainerLocation: PuneQualifications- Bachelor’s or Master’s degree in Computer Science, Data Science, or related field- 3+ years of hands-on AI/ML experience (model development, deployment, or applied research).- 2+ years of experience delivering technical training (classroom or online).- Strong proficiency in Python, ML/DL libraries (TensorFlow, PyTorch, Scikit-learn), and data tools (Pandas, NumPy, SQL).- Familiarity with Generative AI, LLMs, and prompt engineering is highly desirable.- Excellent presentation, communication, and facilitation skills.Preferred Skills- Experience delivering corporate training programs or academic workshops.- Knowledge of cloud ML platforms (AWS Sagemaker, Azure ML, GCP Vertex AI).- Ability to simplify complex technical concepts into easy-to-understand lessons.- Strong problem-solving mindset and learner-first approach.Key Competencies- Engagement-focused: Skilled in keeping learners actively involved.- Clarity of instruction: Can explain complex AI/ML topics with real-world analogies.- Adaptability: Flexible teaching style suited to different learner groups.- Mentorship: Strong inclination to guide, mentor, and motivate learners.- Continuous learner: Keeps up with evolving AI/ML trends and tools.Key ResponsibilitiesTraining Delivery- Conduct live training sessions (in-person, virtual, or hybrid) for diverse groups including students, working professionals, and corporate teams.- Teach core AI/ML topics such as supervised/unsupervised learning, deep learning, NLP, computer vision, generative AI, reinforcement learning, and MLOps.- Guide learners through hands-on coding exercises, model building, and deployment practices.- Facilitate Q&A, discussions, and problem-solving during training to ensure strong concept clarity.- Demonstrate the use of industry-standard tools and frameworks such as Python, TensorFlow, PyTorch, Scikit-learn, Hugging Face, and cloud ML platforms.Learner Engagement & Mentorship- Provide individualized support to learners during training, helping them troubleshoot errors and understand best practices.- Foster an interactive, motivating, and inclusive learning environment.- Mentor learners on mini-projects and capstone assignments to ensure practical application of skills.- Encourage collaboration through group exercises, coding challenges, and hackathon-style workshops.Assessment & Feedback- Evaluate learner performance through quizzes, assignments, and project reviews.- Offer timely, constructive feedback to learners to accelerate their growth.- Collect learner feedback after each session and adjust teaching methods to enhance learning outcomes.Continuous Learning & Adaptation- Stay up-to-date with latest advancements in AI/ML (Generative AI, LLMs, MLOps practices, etc.).- Incorporate trending topics and practical industry use cases into session delivery.- Adapt training content delivery to suit varying learner backgrounds (technical vs. non-technical).


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