À propos de l’offre d’emploi

Mission:

The Engineer DevOps is a pivotal position within MTN, designed for a dynamic and innovative professional who will manage and optimize DevSecOps operations, MLOps operations, and software development processes. This role is crucial in ensuring the seamless integration and deployment of machine learning models, maintaining robust security practices, and driving continuous improvement in software development.

About us:

We at MTN Cameroon are a purpose and value-led organization.

At MTN Cameroon we believe that understanding our people’s needs and aspirations is key to creating experiences that delight you at work, every day. We are committed to fostering an environment where every member of our Y’ello Family is heard, understood, and empowered to live an inspired life. Our values keep us grounded and moving in the right direction. Most importantly, they keep us honest. It is not something we claim to be. It is in our DNA.

As an organisation, we consider it our mission to create an exciting and rewarding place to work, where our people can be themselves, thrive in positivity and ignite their full potential. A workplace that boosts creativity and innovation, improves productivity, and ultimately drives meaningful results. A workplace that is built on relationships and achieving a purpose that is bigger than us. This is what we want you to experience with us!

Our commitments go beyond an organisational promise. It is in our leadership and managerial ethos to meaningfully partner with our employees, customers, and stakeholders with a vision to realise our shared goals.

Our values dubbed, LIVE Y’ello, are the cornerstone of our culture.

Lead with Care

Can-do with Integrity

Collaborate with Agility

Serve with Respect

Act with Inclusion

Responsibilities

DevSecOps Operations:

Establish and maintain CI/CD pipelines to automate the building, testing, and deployment of applications, reducing manual intervention and accelerating release cycles.
Implement security measures, including access controls, encryption, and security monitoring.
Collaborate with cross-functional teams to ensure cohesive and effective cloud infrastructure.

MLOps Operations:

Develop and implement processes for deploying machine learning models into production environments, ensuring scalability and reliability.
Implement monitoring systems to track the performance of machine learning models in production, detecting issues and anomalies.
Optimize the allocation of resources for efficient and cost-effective model inference.

Software Development:

Lead the design and architecture of microservices-based systems.
Implement event-driven patterns to enable real-time communication.
Ensure the development of robust, secure, and scalable software solutions.

Best Practices:

Continuous Integration (CI) and Continuous Deployment (CD): Establish and maintain CI/CD pipelines to automate the building, testing, and deployment of applications, reducing manual intervention and accelerating release cycles.
Model Deployment: Develop and implement processes for deploying machine learning models into production environments, ensuring scalability and reliability.
Scalable Infrastructure: Design and manage scalable infrastructure to support the deployment and inference of machine learning models in real-world applications.
Model Monitoring: Implement monitoring systems to track the performance of machine learning models in production, detecting issues and anomalies.
Data Versioning: Implement data versioning strategies to ensure that changes in training data are tracked and reproducibility is maintained.
Data Drift Management: Implement strategies to monitor and manage data drift, ensuring that machine learning models remain effective over time as input data changes.
Resource Optimization: Optimize the allocation of resources (e.g., CPU, memory) for efficient and cost-effective model inference.
Cost Optimization: Collaborate with finance and operations teams to optimize infrastructure costs while maintaining performance and reliability.

Minimum Job Requirements:

Education:

Minimum of a Bachelor’s Degree in Computer Science, Information Technology, or a related field.
Certification in DevOps in cloud platforms (e.g., AWS Certified Solutions Architect, Azure Solutions Architect) is an advantage.
Fluent in English and French language

Experience:

At least 3 years of experience in DevSecOps operations.
At least 3 years of experience in MLOps operations.
At least 3 years of experience in software development.
Proven experience in managing CI/CD pipelines and deploying machine learning models.
Demonstrated experience in cloud architecture and security

Functional Knowledge:

Continuous Integration (CI) and Continuous Deployment (CD): Establish and maintain CI/CD pipelines to automate the building, testing, and deployment of applications, reducing manual intervention and accelerating release cycles.
Model Deployment: Develop and implement processes for deploying machine learning models into production environments, ensuring scalability and reliability.
Scalable Infrastructure: Design and manage scalable infrastructure to support the deployment and inference of machine learning models in real-world applications.
Model Monitoring: Implement monitoring systems to track the performance of machine learning models in production, detecting issues and anomalies.
Data Versioning: Implement data versioning strategies to ensure that changes in training data are tracked, and reproducibility is maintained.
Data Drift Management: Implement strategies to monitor and manage data drift, ensuring that machine learning models remain effective over time as input data changes.
Resource Optimization: Optimize the allocation of resources (e.g., CPU, memory) for efficient and cost-effective model inference.
Cost Optimization: Collaborate with finance and operations teams to optimize infrastructure costs while maintaining performance and reliability.
Security Measures: Implement security measures, including access controls, encryption, and security monitoring.
Microservices Architecture: Lead the design and architecture of microservices-based system

Skills: