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I need an experienced trainer to run an on-site learning program that blends Generative AI, broader Enterprise AI concepts, and solid Product Engineering practices. The participants will be interns who already code at an intermediate level; they grasp fundamentals but need guidance turning that knowledge into production-ready, AI-enabled features. You should be fully conversant with modern GenAI workflows—prompt engineering, fine-tuning large models, evaluation, and deployment—and be able to frame those topics in a way that links directly to real-world product engineering cycles. If your background also covers classic machine-learning, natural-language processing, or deep-learning stacks, all the better; we want the sessions to feel connected to the wider AI landscape. Deliverables • A concise curriculum (slides + hands-on labs) that spans theory and practical coding • Live, in-person workshops and code-along sessions over an agreed schedule • Simple diagnostic exercises to gauge each intern’s progress and keep the material at the right depth • A brief, written wrap-up with resources and next-step recommendations the team can keep referring to The environment is typical Python-first—think Jupyter, PyTorch or TensorFlow, plus whichever GenAI APIs or frameworks you prefer (OpenAI, Hugging Face, LangChain, etc.). Final acceptance is a smoothly run series of sessions in which the interns can demonstrably build and deploy a small AI-powered feature by themselves. If you enjoy translating complex AI topics into engaging, practical lessons for up-and-coming engineers, let’s set up a quick call to discuss dates and any lab-setup details you might need in advance.
Project ID: 40434994
4 proposals
Active 2 days ago
Location: India
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4 freelancers are bidding on average ₹2,500 INR/hour for this job

Training intermediate developers to ship production AI features is something I genuinely enjoy, and this brief fits exactly what I've been doing. My day job is building AI-powered products, so I don't teach from slides alone. I pull directly from real engineering work — the messy prompt iteration, the fine-tuning decisions that didn't pan out, the deployment gotchas that textbooks skip. That context makes a noticeable difference for interns who already code and need the "why does this matter in production" layer, not another intro-level walkthrough. Here's how I'd structure the program: I'd open with a short diagnostic — a quick coding exercise and a few open questions — to calibrate exactly where the group sits before I touch the curriculum. No point covering what they already know. Every session has a code-along component. I'd use Jupyter, PyTorch or TensorFlow depending on what your stack looks like, and LangChain for anything agentic. Labs are designed so interns leave with something that runs, not just notes. On timeline and pricing — I'd want a 20-minute call first to understand the number of interns, how many days you're thinking, and what lab infrastructure you have in place. That lets me give you a proper schedule and a fixed quote rather than a rough estimate. If the call works, I can usually turn around a draft curriculum within 48 hours so you have something concrete to react to before committing. Want to find a slot this week?
₹2,500 INR in 40 days
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AI/ML Engineer and Web Developer skilled in Python, Machine Learning, Deep Learning, Node.js, and modern web technologies, focused on building intelligent, scalable, and real-world applications including AI security systems, face detection, and automation solutions.
₹2,500 INR in 40 days
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Bengaluru, India
Member since Apr 24, 2026
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