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 Switchâ€Â 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.
Job Summary
We are seeking a highly skilled AI/MLOps Developer to join our team. The ideal candidate will have a strong background in machine learning operations, model deployment, and managing ML pipelines. This role requires a deep understanding of AI/ML workflows and the ability to optimize and maintain AI models in production.
Responsibilities:
- Model Development and Deployment: Design, develop, and deploy machine learning models into production environments, ensuring scalability and reliability.
- Pipeline Automation: Build and maintain automated ML pipelines to streamline model training, testing, and deployment processes.
- Monitoring and Optimization: Monitor deployed models for performance and accuracy, implementing retraining and optimization strategies as needed.
- Infrastructure Management: Manage cloud-based and on-premise infrastructure to support the training and deployment of ML models, ensuring cost efficiency and scalability.
- Security and Compliance: Implement and maintain robust security practices to protect sensitive data and ensure compliance with relevant regulations.
- Collaboration: Work closely with data scientists, software engineers, and other stakeholders to integrate ML models into applications and systems.
- Documentation: Maintain comprehensive documentation of ML pipelines, deployment processes, and model performance metrics.
- Continuous Improvement: Stay updated with the latest advancements in AI/ML and DevOps practices, and apply this knowledge to improve existing systems and processes.
- Troubleshooting: Identify and resolve issues related to model deployment, performance, and infrastructure on time.
Required Qualifications:
- Education: Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent experience.
- Experience: Proven experience in AI/MLOps or a similar role, with hands-on experience in deploying and managing machine learning models.
Technical Skills:
- Proficiency in programming languages such as Python, and familiarity with ML frameworks like TensorFlow, PyTorch, or Scikit-learn.
- Experience with containerization and orchestration tools such as Docker and Kubernetes.
- Knowledge of cloud platforms (AWS, Azure, GCP) and their ML services.
- Familiarity with CI/CD tools and processes for ML pipelines.
- Strong understanding of version control systems (e.g., Git, BitBucket).
- Experience with monitoring and logging tools for model performance tracking.
Preferred Qualifications:
- Experience with advanced topics like distributed training, model explainability, and ethical AI considerations.
- Familiarity with data engineering practices and tools like Apache Spark or Hadoop.
- Contributions to open-source projects related to AI/MLOps.
- Understanding of software development best practices, including Agile methodologies.
Method of Application
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