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MACHINE LEARNING AND OPERATIONS CONSULTANCY (COMPUTER VISION)
Job Location:
Monthly Salary:
Not provided by the employer
Monthly Salary:
Experience Required:
6-10years
Experience Required:
Posted:
10 October 2026 (Yesterday)
Posted:
Application Deadline:
7 January 2027
Application Deadline:
Vacancies:
1 Vacancy
Vacancies:
Job Summary
THE ORGANIZATION
The Alliance of Bioversity International () and the International Center for Tropical Agriculture (CIAT) () delivers research-based solutions that harness agricultural biodiversity and sustainably transform food systems to improve peoples lives. Alliance solutions address the global crises of malnutrition climate change biodiversity loss and environmental degradation.
With novel partnerships the Alliance generates evidence and mainstreams innovations to transform food systems and landscapes so that they sustain the planet drive prosperity and nourish people in a climate crisis.
The Alliance is part of CGIAR a global research partnership for a food-secure future.
Background:
The Alliance of Bioversity International and CIAT leads cutting-edge initiatives leveraging computer vision for plant phenotyping. The objective is to design validate and deploy robust computer vision phenotyping systems capable of operating seamlessly across mobile phones uncrewed aerial vehicles (drones) and rovers within breeding centers across the CGIAR network. By harnessing artificial intelligence and advanced digital phenotyping we aim to modernize conventional breeding approaches and accelerate the development of high-yielding climate-adapted seed varieties of staple food crops.
About the positions:
The consultants will support end-to-end MLOps workflows spanning data ingestion validation dataset versioning model training evaluation deployment monitoring and continuous improvement across both cloud and edge environments. The roles will involve close collaboration with research machine learning software engineering product and field teams to ensure systems are robust maintainable and aligned with project needs.
The consultants will also support the integration of ML systems within the ONA platform a dedicated web- and smartphone-based platform for computer vision phenotyping including deployment workflows connecting mobile applications cloud infrastructure visual data pipelines disease detection and severity scoring workflows backend services and FAIRGrounds-integrated addition the roles will contribute to strengthening best practices around experiment tracking model governance CI/CD workflows deployment automation and ML system monitoring across ONA infrastructure.
These are 11-month full-time consultancy positions (with potential for extension) based at the Alliance office in Arusha Tanzania or Nairobi Kenya.
Key Activities and Specific Terms of Reference
Computer Vision Systems Development and Optimization
Support the development fine-tuning and optimization of robust high-accuracy computer vision models for crop phenotyping across diverse field conditions.
Develop and maintain automated workflows for image data preprocessing quality assurance feature engineering and annotation curation.
Conduct systematic hyperparameter tuning model validation experiments and benchmarking against baseline datasets.
Support the containerization and optimization of inference workflows for low-connectivity edge and resource-constrained environments (e.g. mobile devices edge compute).
Monitor production model performance latency throughput and data/concept drift under variable field lighting and environmental conditions.
Machine Learning Pipeline Development and Maintenance
Develop automate and maintain scalable end-to-end ML pipelines for data ingestion training validation and deployment.
Support the implementation of CI/CD pipelines to streamline automated model updates testing and deployment.
Establish and maintain best practices for version control of datasets code and model artifacts to guarantee full reproducibility.
Collaborate with data engineers software engineers and product teams to integrate ML models into operational production applications.
Disease Detection and Severity Scoring
Support development and deployment of AI workflows for disease detection and severity scoring using field images and visual data.
Implement data and evaluation pipelines for disease annotation validation benchmarking and continuous model improvement.
Support integration of disease scoring workflows within the ONA platform for field-based data collection and analysis.
MLOps Infrastructure and ONA Integration
Develop CI/CD pipelines for model training evaluation and deployment.
Manage experiment tracking model registries and dataset versioning workflows.
Implement monitoring and logging across ML services.
Support deployment of ML services on GCP AWS and related cloud/edge infrastructure.
Support integration of ML services within the ONA platform across mobile backend API and cloud systems.
Ensure compliance with data governance security and responsible AI requirements.
Deliverables and Payment Schedule:
Deliverable 1: Inception Report and Technical Workplan (Month 1 Week 4)
Develop an inception report outlining the technical approach deployment priorities infrastructure requirements integration roadmap and detailed 11-month workplan for MLOps computer vision and disease-scoring workflows across the ONA platform.
Honoraria for Deliverable 1: Tanzanian Shillings / 589762 Kenyan Shillings
Deliverable 2: Implementation of Ingestion Annotation Selection Model Development and Evaluation Pipelines (Month 5 Week 20)
Implement operational workflows and data pipelines focusing on data ingestion annotation selection model training benchmarking and evaluation across cloud and edge environments building on established core MLOps infrastructure.
Honoraria for Deliverable 2: Tanzanian Shillings / 884642 Kenyan Shillings
Deliverable 3: ONA AI Pipeline Integration Breeding Team Support and Trait Model Deployment (Month 8 Week 32)
Deliver integrated deployment workflows connecting ML/CV services with ONA mobile applications APIs backend systems and FAIRGrounds-integrated infrastructure. Assist breeding teams with advanced ML/CV tasks operationalizing and deploying trait extraction models into production alongside monitoring and evaluation documentation.
Honoraria for Deliverable 3: Tanzanian Shillings /Kenyan Shillings
Deliverable 4: Final Technical Report and Handover Package (Month 11 end of assignment)
Submit a final technical report summarizing completed workflows deployed infrastructure model performance across targets key learnings and recommendations for future scaling and maintenance. Deliver finalized documentation deployment guides pipeline configurations and knowledge-transfer materials for internal teams.
Honoraria for Deliverable 4: Tanzanian Shillings /Kenyan Shillings
Requirements
Education:
Bachelors or Masters degree in Computer Science Data Science Artificial Intelligence Software Engineering or a related field.
Technical Competencies:
Experience building and managing ML workflows including model training deployment monitoring and versioning.
Strong programming skills in Python and familiarity with ML frameworks such as PyTorch or TensorFlow.
Experience working with cloud platforms such as GCP AWS or Azure.
Experience with computer vision image-based AI workflows or multimodal AI applications.
Familiarity with containerization technologies (e.g. Docker Kubernetes) and orchestration tools.
Ability to work collaboratively across technical product and field teams.
Strong communication documentation and problem-solving skills.
Background or experience in agriculture digital agriculture or international research environments will be an added advantage.
Benefits
Terms of employment
These are nationally recruited positions based in either Kenya or Tanzania. The initial contract will be for up to 11 Months with the total estimated consultancy amount of Tanzanian Shillings orKenyan Shillings.
Applications
Applicants are invited to visit to get full details of the position and to submit their applications. Applications MUST include reference number Ref: MACHINE LEARNING AND OPERATIONS CONSULTANCY (COMPUTER VISION) as the position applied for. Application including CV technical proposal and financial proposal should be saved as one document using the candidates last name first name for ease of sorting.
Note: The Alliance does not charge a fee at any stage of the recruitment process (application interview meeting processing or training). The Alliance also does not concern itself with information on applicants bank accounts.
Applications closing date: 30 October 2026
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:
Required Skills:
Experience building and managing ML workflows including model training deployment monitoring and versioning. Strong programming skills in Python and familiarity with ML frameworks such as PyTorch or TensorFlow. Experience working with cloud platforms such as GCP AWS or Azure. Experience with computer vision image-based AI workflows or multimodal AI applications. Familiarity with containerization technologies (e.g. Docker Kubernetes) and orchestration tools. Ability to work collaboratively across technical product and field teams. Strong communication documentation and problem-solving skills. Background or experience in agriculture digital agriculture or international research environments will be an added advantage.
Required Education:
Bachelors or Masters degree in Computer Science Data Science Artificial Intelligence Software Engineering or a related field.
