Machine Learning Operations Specialist - CIMMYT

Responsibilities and Duties

MLOps Framework Development and Pipeline Automation

• Design and implement CI/CD pipelines and scalable MLOps frameworks.
• Develop and maintain data, training, and deployment pipelines ensuring reproducibility and efficiency.

Model Deployment, Monitoring, and Performance Optimization

• Deploy machine learning models into production and ensure reliable performance.
• Implement monitoring, logging, and alerting systems to track model accuracy and drift.

Image-Based AI and Digital Phenotyping Solutions

• Support development and deployment of image recognition models using drone and mobile imagery.
• Utilize tools such as Roboflow and Databricks for image-based workflows and scalable ML operations.

Collaboration and Cross-Institutional Integration

• Work with CGIAR partners (e.g., ICRISAT, IITA) and internal teams to harmonize MLOps practices.
• Facilitate knowledge sharing and integration across multidisciplinary teams.

Governance, Capacity Building, and Continuous Improvement

• Ensure compliance with data governance, security, and privacy standards.
• Provide training and promote adoption of best practices while integrating emerging MLOps technologies.

Requirements and Qualifications

• Bachelor’s degree in Computer Science, Data Science, Artificial Intelligence, Software Engineering, Agricultural Informatics, or a related quantitative field.
• Minimum 1–3 years of relevant experience in machine learning, data science, or MLOps environments.
• Demonstrated understanding of machine learning workflows, including data preprocessing, model training, evaluation, deployment, and monitoring.
• Experience working with machine learning models, deep learning frameworks, and Large Language Models (LLMs) in research or production settings.
• Experience working within international research organizations, CGIAR centers, or agricultural research projects will be an added advantage.

How to Apply

Interested and qualified candidates are encouraged to apply by visiting the official CIFOR-ICRAF website at www.cifor-icraf.org before the application deadline.