Machine Learning Operations Specialist – CIMMYT at Center for International Forestry Research (CIFOR)

Duties and responsibilities

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.

Requirements

• 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.

Education, knowledge and experience

• 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.

Terms and conditions

• This is a Locally Recruited Staff (LRS) position. CIFOR-ICRAF offers a competitive remuneration package commensurate with experience and qualifications. In Kenya, employment contracts are issued under ICRAF in compliance with Kenyan labour law. Locally recruited staff are eligible for a non-contributory pension scheme, comprehensive medical insurance, paid annual and statutory leave, and learning and development opportunities in line with CIFOR-ICRAF policies.
• The appointment will be for a period of two (2) years, inclusive of a six-month probationary period, with the possibility of extension contingent upon performance, continued relevance of the position and available resources.
• The duty station will be in Nairobi, Kenya.
• We will acknowledge all applications but will only contact short-listed candidates.

End Date: 11th June 2026