Machine Learning Operations Specialist – CIMMYT

Reference number: 202625
Job status: In-progress
Job category: Local Position
Duty station: Nairobi, Kenya
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CIFOR-ICRAF
The Center for International Forestry Research (CIFOR) and World Agroforestry (ICRAF) envision a more equitable world where trees in all landscapes, from drylands to the humid tropics, enhance the environment and well-being for all. CIFOR and ICRAF are non-profit science institutions that build and apply evidence to today’s most pressing challenges, including energy insecurity and the climate and biodiversity crises. Over a combined total of 65 years, we have built vast knowledge on forests and trees outside of forests in agricultural landscapes (agroforestry). Using a multidisciplinary approach, we seek to improve lives and to protect and restore ecosystems. Our work focuses on innovative research, partnering for impact, and engaging with stakeholders on policies and practices to benefit people and the planet. Founded in 1993 and 1978, CIFOR and ICRAF are members of CGIAR, a global research partnership for a food secure future dedicated to reducing poverty, enhancing food and nutrition security, and improving natural resources.

Overview

About our organization: CIMMYT is a cutting edge, non-profit, international organization dedicated to solving tomorrow's problems today. It is entrusted with fostering improved quantity, quality, and dependability of production systems and basic cereals such as maize, wheat, triticale, sorghum, millets, and associated crops through applied agricultural science, particularly in the Global South, through building strong partnerships. This combination enhances the livelihood trajectories and resilience of millions of resource-poor farmers, while working towards a more productive, inclusive, and resilient agrifood system within planetary boundaries. For more information, visit: cimmyt.org In Kenya, CIMMYT is hosted by World Agroforestry (ICRAF), a member of the CGIAR that is headquartered on United Nations Avenue, Nairobi, Kenya. We invite you to learn more about CIMMYT and World Agroforestry by accessing our web sites: www.cimmyt.org and www.worldagroforestry.org CIMMYT is looking for a: Machine Learning Operations Specialist The MLOps Specialist will establish and manage scalable machine learning operations to ensure efficient development, deployment, and monitoring of AI models, with a focus on supporting digital phenotyping and data-driven agricultural research. The role will enable the integration of image-based AI solutions using drone and mobile data into production systems. It will also strengthen collaboration across CGIAR centers by standardizing MLOps practices and infrastructure. Additionally, the position will contribute to building reliable, reproducible, and secure data and model pipelines aligned with institutional data governance standards.

Duties and responsibilities

1. 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.

2. 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.
  

3. 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.

4. 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.

5. 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.

Application process

The application deadline is 11 Jun 2026
We will acknowledge all applications, but will contact only short-listed candidates.