ML / DevOps Engineer Lead at National Agency for Science and Engineering Infrastructure (NASENI)

The National Agency for Science and Engineering Infrastructure (NASENI) was established in 1992 by the Federal Government after the recommendations of the White Paper Committee on the 1991 Report of a 150 member National Committee on Engineering Infrastructure comprising Scientists, Engineers, Administrators, Federal and State Civil Servants, Economists, Lawyers, Bankers and Industrialists.

The mandate of NASENI is specifically in the area of Capital goods, research, production and reverse engineering. NASENI, by its mandate and scope of operation is the Nigerian only purpose built Agency designed to conduct developmental work in the areas of manufacturing and as such, it is capable of coordinating the proliferation of technologies developed either within or outside of its Centers including patents obtained. Technologies developed in the areas of spares, components and systems engineering are to be transferred to Entrepreneurs for the production of goods and services.

We are recruiting to fill the position below:

Job Title: ML / DevOps Engineer Lead

Location: Abuja
Job type: Full time (Onsite)

Role Overview

• The ML / DevOps Engineer Lead is responsible for operationalizing AI systems through robust MLOps practices, ensuring models move reliably from research into production.
• This role bridges data science, engineering, and infrastructure to enable scalable, secure, and high-performance AI deployments.

Key Responsibilities

• Responsible for building and managing CI/CD pipelines for ML model training, deployment, and monitoring.
• Responsible for designing scalable, reliable ML infrastructure and technical architecture.
• Responsible for overseeing model performance monitoring, drift detection, and continuous improvement.
• Responsible for implementing infrastructure-as-code, automated testing, and MLOps best practices.
• Responsible for leading and coordinating a technical sub-team delivering production-grade AI systems.

Required Experience & Skills
Required:

• Strong experience in MLOps, DevOps, and cloud or hybrid infrastructure.
• Hands-on expertise deploying and maintaining ML systems in production.
• Proficiency with CI/CD pipelines, monitoring tools, and automation frameworks.

Desirable:

• Experience supporting AI systems in regulated or mission-critical environments.
• Familiarity with data security and compliance considerations.

Application Closing Date
Not Specified.

How to Apply
Interested and qualified candidates should:
Click here to apply online