Technical Trainer AI/ML, AIOps & MLOps - Freelance AI/M (Part time / Training Partner)

**Job Description – Freelance AI/ML, AIOps & MLOps Trainer**

**Position :- Freelance AI/ML, AIOps & MLOps Trainer**

**Experience :- Minimum 4+ years of relevant industry/training experience**

**Engagement Type :- Freelancer**

**Per Hour - 900 to 1300**

**Role Overview**

We are looking for an experienced **AI/ML, AIOps & MLOps Trainer** to deliver practical, industry-oriented training covering Artificial Intelligence, Machine Learning, AI-driven IT Operations, and Machine Learning Operations. The trainer should have strong hands-on experience in developing, deploying, monitoring, and managing AI/ML solutions in real-world environments.

**Key Responsibilities**

• Deliver instructor-led training on **AI/ML, AIOps, and MLOps**.
• Explain concepts from foundation to advanced level using practical examples.
• Conduct hands-on coding, model development, deployment, and monitoring activities.
• Guide learners through real-world AI/ML and MLOps projects.
• Demonstrate AI-driven IT operations, monitoring, automation, and incident management.
• Teach ML model deployment, versioning, CI/CD, monitoring, and lifecycle management.
• Conduct assessments, coding exercises, and practical technical activities.
• Support learners with debugging, troubleshooting, and problem-solving.
• Follow the provided course structure, session plan, and learning outcomes.
• Provide learner feedback and coordinate with the training team.

**Required Technical Skills**

• **Python & Machine Learning**
• **Data Preprocessing & Feature Engineering**
• **Supervised & Unsupervised Learning**
• **Deep Learning fundamentals**
• **TensorFlow / PyTorch / Scikit-learn**
• **AIOps & IT Operations**
• **Monitoring & Observability**
• **Anomaly Detection & Event Correlation**
• **Root Cause Analysis & Automation**
• **Git & GitHub**
• **Docker & Kubernetes**
• **CI/CD Pipelines**
• **MLflow / Experiment Tracking**
• **Model Deployment & Monitoring**
• **Cloud – AWS / Azure / GCP**
• Basic knowledge of **Generative AI & LLMs**

**Preferred Skills**

• Experience with real-world AI/ML, AIOps, or MLOps implementations.
• Strong knowledge of **DevOps, Cloud, Kubernetes, and CI/CD**.
• Experience with tools such as **MLflow, Kubeflow, Airflow, Grafana, Prometheus, Splunk, Dynatrace, or similar platforms**.
• Experience training college students or working professionals.
• Strong communication, presentation, and mentoring skills.
• Ability to explain complex technical concepts in a simple and practical manner.

**Eligibility**

• **Minimum 4+ years of relevant AI/ML, AIOps, MLOps, ML Engineering, DevOps, or Cloud experience.**
• Strong hands-on knowledge of AI/ML and production deployment practices.
• Prior experience as an **AI/ML Engineer, MLOps Engineer, AIOps Engineer, DevOps Engineer, Data Scientist, or Technical Trainer** is preferred.

**Key Competencies**

**AI/ML | AIOps | MLOps | Python | Machine Learning | Deep Learning | Generative AI | Docker | Kubernetes | CI/CD | Cloud | Model Deployment | Monitoring & Observability | Automation | Training & Mentoring**