Machine Learning and Operations Consultant

About the role

The consultancy supports the NDIZI project to develop, deploy, and operationalize machine learning systems for the SIKIA AI platform, enabling crop improvement and field data collection across speech, NLP, and multimodal pipelines.

Key responsibilities

• Design and maintain end‑to‑end MLOps workflows covering data ingestion, validation, versioning, model training, evaluation, deployment, monitoring, and continuous improvement on cloud and edge environments.
• Refine multilingual ASR pipelines, implement automated retraining with field data, and optimize inference for low‑connectivity settings.
• Develop multimodal pipelines linking speech, transcripts, metadata, and images; manage dataset versioning and annotation.
• Build AI workflows for disease detection and severity scoring, integrating them into the SIKIA and ONA platforms.
• Implement CI/CD pipelines, experiment tracking, model registries, and monitoring across GCP, FAIRGrounds, and related infrastructure.

Required profile

• Master’s degree in Computer Science, Data Science, AI, Software Engineering or related field.
• At least 3 years of experience in machine learning engineering, MLOps, or AI system deployment.
• Demonstrated ability to work collaboratively with research, software, product, and field teams.

Required skills

• Python programming
• Experience with MLOps tools and CI/CD pipelines
• Knowledge of speech and NLP systems, including multilingual ASR
• Familiarity with multimodal AI pipelines and visual‑language models
• Proficiency with cloud platforms (GCP) and edge deployment
• Experience with model monitoring, versioning, and governance