AI Engineering Trainer

Company Description

HubotX Labs Private Limited specializes in next-generation consulting and enterprise operations enablement with a focus on establishing and scaling Global Capability Centers (GCCs) in India. By combining deep domain expertise with AI-driven automation and people intelligence, HubotX delivers innovative, future-focused solutions. The company provides end-to-end support across strategy, talent, operations, and compliance. HubotX is committed to helping global enterprises achieve scalable and impactful growth with custom solutions tailored to their needs.

Role Overview

We are looking for an experienced AI Engineering Trainer who can design and deliver an end-to-end, industry-ready AI curriculum for engineering students. This role goes beyond teaching theory. The trainer must bring real-world experience in building, deploying, and scaling AI systems, and should be capable of preparing students for production environments, certifications, and industry interviews.

The ideal candidate is hands-on, comfortable with modern AI stacks including Generative AI, and able to mentor students to think like professional AI engineers.

Key Responsibilities

Deliver structured training across core AI, Machine Learning, Deep Learning, Generative AI, and MLOps

Teach using real-world datasets, case studies, and production scenarios

Guide students through end-to-end projects including data handling, model building, deployment, and monitoring

Design and evaluate hands-on assignments, coding challenges, and capstone projects

Prepare students for industry-standard certifications such as AWS, Azure, Google ML, and GenAI certifications

Conduct technical reviews, code walkthroughs, and project defenses

Mentor students on GitHub portfolio building, system design thinking, and interview readiness

Stay updated with evolving AI tools, frameworks, and industry practices

Collaborate with curriculum designers to continuously improve course content

Technical Skills Required

Core AI & ML

Strong expertise in Machine Learning algorithms and model evaluation

Hands-on experience with Deep Learning architectures such as CNNs, RNNs, Transformers

Solid understanding of statistics, probability, and applied mathematics for AI

Programming & Frameworks

Advanced proficiency in Python

Experience with PyTorch and TensorFlow

Strong knowledge of scikit-learn, Pandas, NumPy

Generative AI

Practical experience with Large Language Models

Prompt engineering, RAG architectures, and fine-tuning approaches

Familiarity with OpenAI APIs, LangChain, LlamaIndex or similar tools

MLOps & Deployment

Experience deploying ML models using Flask or FastAPI

Understanding of Docker and basic CI/CD concepts

Exposure to cloud platforms such as AWS, Azure, or GCP

Familiarity with model monitoring, versioning, and retraining strategies

Responsible AI

Awareness of AI ethics, bias, explainability, and governance

Understanding of AI security risks and mitigation techniques

Teaching & Mentoring Skills

Ability to explain complex AI concepts in a simple, structured manner

Strong classroom presence and student engagement skills

Experience training engineering students or working professionals

Capability to mentor students with different learning speeds

Strong communication and documentation skills

Preferred Qualifications

Bachelors degree in Engineering (B.E. / B.Tech) is mandatory

Preferred engineering disciplines include:

• Computer Science
• Information Technology
• Electronics and Communication
• Electrical Engineering
• Artificial Intelligence or Data Science

A Masters degree (M.E. / M.Tech / MS) in a relevant engineering or AI-related field is a strong plus

8+ years of industry experience in AI, ML, or Data Science roles

Prior experience as a trainer, mentor, or technical lead

Industry certifications in AI or cloud platforms are a strong plus

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