THE ORGANIZATION

The Alliance of Bioversity International & CIAT delivers research-based solutions that harness agricultural biodiversity and sustainably transform food systems to improve people’s lives. Alliance solutions address the global crises of malnutrition, climate change, biodiversity loss, and environmental degradation.

The Alliance works with local, national, and multinational partners across Sub Saharan Africa, Latin America and the Caribbean and Asia, and with public and private sectors. The Alliance is part of CGIAR, a global research partnership for a food-secure future, dedicated to reducing poverty, enhancing food and nutrition security, and improving natural resources and ecosystem services.

Background of the position

The Alliance of Bioversity International and CIAT have initiated a project, titled Artemis. Artemis is developing AI technology to enable on-farm breeding. Crop breeding is one of the foundations of agriculture, under the current breeding systems a common assumption is that it takes 10 years to develop a new variety. Given the pace of climate change this timeframe is no longer viable. New approaches are needed to speed up the breeding cycle and enable a greater synchrony between plant breeding and on-farm conditions, shifting breeding from a majority on-station to majority on-farm process. Artemis is addressing this issue by leveraging the power of technology to enable breeding programs with a new generation of AI-powered and smartphone-deployable tools. The principal technology is computer vision phenotyping, with explorations into multimodal data that integrates speech and text to actively integrate farmers into the plant improvement process. Artemis is currently in the second investment phase, having been featured recently in Reuters.

The Research Specialist will lead the implementation and continuous improvement of Machine Learning Operations (MLOps) processes and infrastructure. They will collaborate with cross-functional teams to ensure the seamless deployment, monitoring, and maintenance of machine learning models in production environments.

Key duties & responsibilities

• Design and implement MLOps strategies and frameworks (CI/CD pipelines) to streamline the development, deployment, and monitoring of machine learning models.
• Collaborate with data scientists, software engineers, and DevOps teams to deploy and operationalize machine learning models in production environments.
•  Develop and maintain scalable and reliable pipelines for data preprocessing, feature engineering, model training, and model serving.
• Establish and maintain best practices for version control, model reproducibility, and model performance tracking.
• Implement and manage infrastructure for model monitoring, logging, and alerting to ensure the reliability and performance of deployed models.
• Automate testing and validation processes to ensure the accuracy and robustness of machine learning models.
• Collaborate with IT and security teams to ensure data privacy, compliance, and security standards are met throughout the MLOps lifecycle.
• Provide technical guidance and training to internal teams on MLOps practices and tools.
•  Stay up-to-date with the latest trends and advancements in the MLOps field.

Requirements

• Master’s degree in Computer Science, Engineering, or a related field.
• A formal background in one or more of the following: Computer Science, Data Science, Software Engineering, Data Engineering, Statistics, Mathematics
• Strong hands-on experience with machine learning frameworks and tools such as TensorFlow, PyTorch, or scikit-learn.
• Proficiency in programming languages like Python, as well as experience with software development practices and version control systems.
• Solid understanding of cloud computing platforms (e.g., AWS, Azure, GCP) and experience with deploying machine learning models in cloud environments.
• Familiarity with containerization technologies (e.g., Docker, Kubernetes) and orchestration tools.
• Knowledge of data engineering principles, including data preprocessing, feature engineering, and data pipeline development.
• Strong problem-solving skills and the ability to work in a collaborative environment.
• Ability to analyze data, identify patterns, and draw meaningful conclusions while ensuring accuracy and thoroughness in research and data collection.
• Ability to think outside the box to develop innovative research approaches and solutions.

Terms of employment

This is a nationally recruited position based in either Nairobi, Kenya or Arusha, Tanzania. The initial contract will be for one year subject to a probation period of three months and is renewable depending on performance and availability of resources. This position is graded at BG08 level in a scale of BG01 to BG14 (BG14 being the highest level according to the Alliance job classification framework policy). We offer a competitive salary and excellent benefits including but not limited to insurance, retirement plan, staff training and development, paid time off and flexible working arrangements.

The Alliance Bioversity-CIAT is committed to fair, safe, and inclusive workplaces. We believe that diversity powers our innovation, contributes to our excellence, and is critical for our mission. Recruiting and mentoring staff to create an inclusive organization that reflects our global character is a priority. We encourage applicants from all cultures, races, colors, religions, sexes, national or regional origins, ages, disability statuses, sexual orientations, marital status, and gender identities. Female candidates are strongly encouraged to apply.

Applications

Applicants are invited to visit https://alliancebioversityciat.org/careers to get full details of the position and to submit their applications. Applications MUST include reference number RFPxxxxx – Research Specialist-MLOPS as the position applied for. Cover letter and CV should be saved as one document using the candidate’s last name, first name for ease of sorting. The Alliance collects and process personal data in accordance with applicable data protection laws.

Applications closing date: 4^th July 2024

Please note that email applications will not be considered.

Only short-listed candidates will be contacted.

We invite you to learn more about us at:  http://alliancebioversityciat.org