Machine Learning and Operations Consultant Job at Alliance of Bioversity International an…
AI summary
The Alliance of Bioversity International and CIAT seeks an MLOps Consultant to develop and deploy AI solutions for the SIKIA platform in agricultural research. Responsibilities include ASR systems, LLM workflows, multimodal AI, and CI/CD pipelines. Requires a Master's in Computer Science or related field.
- Focus on agriculture and AI integration
- Multilingual ASR and LLM deployment
- Work in Arusha, Tanzania
- Full-time consultant role
AI job guide
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AI salary guide
Not enough public dataNot enough public salary data is available for this exact role. Before applying, prepare to ask about gross pay, benefits, contract length, probation period, transport and any allowances.
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- UnclearRelated work experienceThe text mentions experience, but the exact level should be confirmed at source.
- RequiredEducation or certification mentioned in the postThe captured text mentions education, a diploma, certificate, or licence.
- PreferredPractical evidence in security, internship, segurancaThe tags and summary point to skills connected with this role.
- RequiredAvailability to work in ArushaThe vacancy is associated with this location.
- UnclearComfort with the Full Time contract termsConfirm hours, duration, probation and benefits at the original source.
Documents to prepare
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- Role specificCover letter or short employer message
- OptionalProfessional references
- Role specificAcademic or professional certificates
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Application tips for this job
- Place your strongest Machine Learning and Operations Consultant Job at Alliance of Bioversity International an… evidence in the first half of your CV.
- In your cover letter or employer message, connect your experience to Alliance of Bioversity International and CIAT and the role in Arusha.
- Add concrete examples related to security, internship, seguranca, ideally with measurable outcomes or clear responsibilities.
- Follow the instructions from AjiraPulse Tanzania; avoid sending documents to unofficial contacts or copied links.
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Source and safety check
- AjiraPulse Tanzania
- Original source link available
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- Deadline not specified
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Interview preparation
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Original source description
Full Time Machine Learning and Operations Consultant Job at Alliance of Bioversity International and CIAT Posted 1 month ago by Alliance of Bioversity International and CIAT Arusha Job Description The Alliance of Bioversity International and CIAT is seeking a highly motivated and technically skilled Machine Learning and Operations (MLOps) Consultant to support the development, deployment, and operationalization of advanced artificial intelligence solutions within the SIKIA platform. SIKIA is a voice-first and multimodal AI system designed to support agricultural research, crop improvement programs, and field-based decision-making through innovative technologies including speech recognition, natural language processing, multimodal AI, and agentic workflows. This role offers an exciting opportunity for AI and machine learning professionals to work at the intersection of technology, agriculture, and international research. The successful candidate will help transform machine learning research into scalable real-world applications, supporting digital agriculture initiatives and improving the connection between crop breeding programs and farming communities across diverse environments.
Responsibilities
Support deployment and optimization of multilingual Automatic Speech Recognition (ASR) systems for cloud and mobile platforms. Develop workflows for speech data collection, transcription, evaluation, and continuous model improvement. Implement automated model retraining and fine-tuning pipelines using newly collected field data. Support deployment of Large Language Model (LLM) workflows for conversational analysis and trait extraction. Monitor machine learning models for performance, latency, reliability, and data drift in field environments. Optimize AI inference workflows for low-connectivity and resource-constrained environments. Develop multimodal AI pipelines integrating speech, text transcripts, metadata, and field images. Implement workflows for multimodal data validation, annotation, synchronization, storage, and dataset versioning. Support training, evaluation, and deployment of multimodal and visual-language models. Develop scalable systems for managing large multimodal datasets and AI outputs on cloud infrastructure. Support benchmarking, reproducibility, and optimization of AI workflows for field deployment. Contribute to AI-based disease detection and severity scoring systems using field images and multimodal data. Develop data pipelines for disease annotation, validation, benchmarking, and continuous model improvement. Integrate disease detection workflows within SIKIA and ONA platforms for field-based data collection and analysis. Build and maintain CI/CD pipelines for model training, testing, evaluation, and deployment. Manage experiment tracking systems, model registries, and dataset versioning frameworks. Implement monitoring, logging, and observability solutions across machine learning services. Collaborate with software engineers to integrate Retrieval-Augmented Generation (RAG) pipelines into agentic AI architectures. Deploy and manage machine learning services on Google Cloud Platform (GCP), FAIRGrounds, and related infrastructure. Integrate machine learning services with mobile applications, APIs, backend systems, and cloud platforms. Ensure compliance with data governance, privacy, security, and responsible AI requirements. Qualifications: Master’s Degree in Computer Science, Data Science, Artificial Intelligence, Software Engineering, or a related field. Strong academic foundation in machine learning, software engineering, and data systems. Additional certifications in cloud computing, machine learning, or DevOps are advantageous.
Experience
Minimum of three (3) years of
in Machine Learning Engineering, MLOps, or AI deployment. Proven
building, deploying, monitoring, and maintaining machine learning systems.
working with machine learning lifecycle management, model versioning, and deployment workflows. Practical
deploying AI applications in production environments.
working with cloud-based machine learning infrastructure. Exposure to agricultural technology, digital agriculture, or international research projects is an advantage.
with machine learning frameworks such as PyTorch or TensorFlow. Knowledge of cloud platforms including Google Cloud Platform (GCP), AWS, or Microsoft Azure. Expertise in machine learning operations (MLOps) principles and practices. Strong understanding of Natural Language Processing (NLP), speech recognition technologies, and conversational AI.
working with Large Language Models (LLMs) and generative AI systems. Knowledge of multimodal AI, computer vision, and image-processing workflows.
implementing CI/CD pipelines and DevOps practices for AI systems. Understanding of model monitoring, observability, logging, and performance optimization. Familiarity with data governance, security, and responsible AI frameworks. Strong analytical and problem-solving abilities. Excellent communication and technical documentation skills. Ability to collaborate effectively with multidisciplinary teams. General
with cutting-edge technologies including MLOps, Large Language Models, multimodal AI, speech technologies, computer vision, cloud infrastructure, and agentic AI systems. The expertise developed in this role can lead to future career opportunities such as Senior Machine Learning Engineer, MLOps Lead, AI Solutions Architect, Data Science Manager, AI Product Manager, Head of AI Engineering, Research Scientist, or Director of Artificial Intelligence within global technology, research, agricultural, and innovation organizations. Share Link: Application deadline closed.
Knowledge and Skills
Strong programming skills in Python.
Requirements
Passion for applying AI technologies to real-world agricultural and research challenges. Ability to work effectively in cross-functional and multicultural environments. Strong attention to detail and commitment to quality. Ability to manage multiple projects and priorities simultaneously. Commitment to continuous learning and staying current with emerging AI technologies. Strong organizational and project management skills. Ability to work independently while contributing effectively to team objectives. Professionalism, integrity, and adherence to ethical AI practices. This position offers an outstanding opportunity for career advancement in artificial intelligence, machine learning operations, and digital innovation. As a Machine Learning and Operations Consultant, you will gain hands-on