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Machine Learning Operations (MLOps) Engineer at InterSwitch

InterSwitchLagos, Nigeria Cybersecurity
Full Time
Interswitch Limited is an integrated payment and transaction processing company that provides technology integration, advisory services, transaction processing and payment infrastructure to government, banks and corporate organizations. Interswitch, through its “Super Switch” provides online, real-time transaction switching that enable businesses and individuals have access to their funds across the 24 banks in Nigeria and across a variety of payment channels such as Automated Teller Machines (ATMS), Point of Sale (PoS) terminals, Mobile Phones, Kiosks, Web and Bank Branches.


  • The ideal candidate will be responsible for supporting and enhancing Interswitch’s machine learning operations (MLOps) ecosystem.
  • He/she will ensure the seamless deployment, monitoring, and optimization of machine learning models while enabling data scientists and engineers to deliver innovative AI/ML solutions.


  • Deploy and manage machine learning models and pipelines, automate deployment processes, and monitor model performance in production environments.
  • Collaborate with the infrastructure team to provision, configure, and maintain the necessary resources for machine learning workloads.
  • Implement and maintain CI/CD pipelines for ML projects, ensuring seamless and efficient deployment processes.
  • Monitor and optimize model performance, scaling resources as needed to accommodate increased workloads and maintain system stability.
  • Maintain version control for machine learning models and associated codebase using industry-standard tools (e.g., Git).
  • Work closely with data scientists, data engineers, data analysts, software engineers, and other cross-functional teams to ensure successful model deployments and integration.
  • Adhere to security best practices and compliance requirements, ensuring data privacy and protection.
  • Create and maintain documentation for MLOps processes and workflows.
  • Diagnose and resolve issues related to machine learning pipelines, infrastructure, and deployments.


  • Bachelor's degree in Computer Science, Engineering, or a related field.


  • Minimum of 2 years in data science and/or 1-2 years in DevOps role.
  • 1-2 years in a data role for reporting purposes such as operations reporting, statistics, etc.

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