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