Dev & MLOps Mentor

Big Brains; Pakistan; Remote; PKR 1,200,000 - 1,800,000; Part time

Benefits offered by this job

Mentoring portfolio

Future course creation

Job summary

Big Brains Learning is seeking an experienced DevOps and MLOps mentor to design and deliver practical course content for university students and aspiring engineers. The selected candidate will teach students how to automate development workflows, deploy applications, manage infrastructure and build reliable machine learning deployment pipelines.

You will teach CI/CD, Docker, Kubernetes, cloud deployment and ML model pipelines, mentor projects, review work, and coordinate with the team to shape

Qualifications

• Strong practical experience in DevOps and MLOps.
• Solid understanding of CI/CD and deployment automation.
• Experience with Docker and preferably Kubernetes.
• Understanding of cloud infrastructure and monitoring.
• Experience deploying machine learning models is a plus.
• Ability to explain DevOps and MLOps concepts clearly.

Responsibilities

• Design and structure DevOps and MLOps course content according to an agreed curriculum.
• Deliver clear and practical DevOps and MLOps lessons.
• Teach Git and collaborative development workflows.
• Explain CI/CD concepts and automation.
• Teach Docker and containerization.
• Introduce Kubernetes and container orchestration where applicable.
• Teach cloud deployment and infrastructure fundamentals.
• Explain monitoring, logging and application reliability.
• Teach machine learning model packaging and deployment.
• Explain ML pipelines, experiment tracking and model versioning.
• Teach model monitoring and lifecycle management.
• Demonstrate practical CI/CD and ML deployment workflows.
• Guide students through practical DevOps and MLOps projects.
• Review student work and provide constructive feedback.
• Answer student questions related to DevOps and MLOps.
• Coordinate with the Big Brains team regarding curriculum and student progress.

Skills

DevOps

MLOps

CI/CD

Cloud

Monitoring

ML pipelines

Model deployment

Mentoring

Tools

Docker

Kubernetes

CI/CD automation

Job description

Big Brains Learning is a student-focused learning and career platform helping university students Learn, Build and Launch through practical courses, internships, projects, notes and career opportunities.

Company: Big Brains LearningPosition: Dev & MLOps MentorEmployment Type: Contract BasedWork Mode: RemoteDepartment: DevOps & MLOpsContract Duration: Project or Contract Based

Role Overview

Big Brains Learning is looking for an experienced DevOps and MLOps professional and mentor who can create and deliver practical DevOps and machine learning operations course content for university students and aspiring engineers. The selected candidate will teach students how to automate development workflows, deploy applications, manage infrastructure and build reliable machine learning deployment pipelines.

Key Responsibilities

• Design and structure DevOps and MLOps course content according to an agreed curriculum.
• Deliver clear and practical DevOps and MLOps lessons.
• Teach Git and collaborative development workflows.
• Explain CI/CD concepts and automation.
• Teach Docker and containerization.
• Introduce Kubernetes and container orchestration where applicable.
• Teach cloud deployment and infrastructure fundamentals.
• Explain monitoring, logging and application reliability.
• Teach machine learning model packaging and deployment.
• Explain ML pipelines, experiment tracking and model versioning.
• Teach model monitoring and lifecycle management.
• Demonstrate practical CI/CD and ML deployment workflows.
• Guide students through practical DevOps and MLOps projects.
• Review student work and provide constructive feedback.
• Answer student questions related to DevOps and MLOps.
• Coordinate with the Big Brains team regarding curriculum and student progress.

Course Content

The course may cover Git, CI/CD, Docker, Kubernetes, cloud deployment, infrastructure fundamentals, monitoring, logging, ML model deployment, experiment tracking, model versioning, ML pipelines, model monitoring and practical DevOps/MLOps projects.

Deliverables

The mentor will deliver agreed course sessions and learning materials and may provide Docker projects, CI/CD exercises, deployment labs, ML pipelines, assignments and project reviews.

Contract and Payment

This is a contract based position. Compensation will be mutually agreed upon according to the course scope, duration and responsibilities. Payment may be based on individual sessions, milestones, complete course delivery or another mutually agreed arrangement.

RequirementsStrong practical experience in DevOps and MLOps.Strong understanding of CI/CD and deployment automation.Experience with Docker and preferably Kubernetes.Understanding of cloud infrastructure and monitoring.Experience deploying machine learning models will be an advantage.Understanding of ML pipelines, experiment tracking and model lifecycle management.Ability to explain DevOps and MLOps concepts clearly.Strong communication and mentoring skills.Ability to guide students through practical projects.Previous teaching or mentoring experience will be considered an advantage.

Student Mentoring

The mentor should focus on practical engineering workflows and help students understand how applications and machine learning systems move from development to production.

Quality Review

Course content may be reviewed by the Big Brains team to ensure technical accuracy and educational quality.

Confidentiality

The mentor agrees to maintain confidentiality regarding non-public information received from Big Brains.

Termination

Either party may terminate the contract according to the termination conditions specified in the final agreement.

Benefits

Opportunity to mentor university students. Opportunity to build a professional DevOps and MLOps teaching portfolio. Potential for future course creation and mentoring contracts. Opportunity to collaborate with Big Brains on software and AI education projects.

Big Brains LearningLearn, Build and Launch

Requirements

• Strong practical experience in DevOps and MLOps.
• Strong understanding of CI/CD and deployment automation.
• Experience with Docker and preferably Kubernetes.
• Understanding of cloud infrastructure and monitoring.
• Experience deploying machine learning models will be an advantage.
• Understanding of ML pipelines and model lifecycle management.
• Ability to explain DevOps and MLOps concepts clearly.
• Strong communication and mentoring skills.
• Ability to guide students through practical projects.
• Previous teaching or mentoring experience will be considered an advantage.