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AI/MLOps Developer at Interswitch (On-Site)

Full Time | Senior Role | Nigeria

Job Posting

Trendy Campus Job Post
  Staff Strength: 1 - 5 Staffs

Description

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.

Qualifications

  • 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.

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.

Benefits

  • Benefit will be made available at the point of qualification.
  • Method of Application
  • Interested and qualified? Go to Interswitch on www.linkedin.com to apply
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 Posted: 9/11/2024