Researcher in Machine Learning and MLOPS (2 Year Full Time Fixed-term Contract)

In brief

**Overview** This is a 2-year full-time fixed-term contract position for a Researcher in Machine Learning and MLOPS at the University of the Witwatersrand. The role is hosted within the School of Statistics and Actuarial Science, which is engaged in a growing research programme focused on AI for climate risk modelling and climate intelligence, supported by the Bezos Earth Fund. This programme specifically develops machine learning methods for weather forecasting, climate risk modelling, and climate-impact analytics relevant to African institutions. The successful candidate will operate at the intersection of machine learning engineering, atmospheric science, and large-scale geospatial data systems, supporting the development and deployment of machine learning models for weather and climate prediction. Key areas of focus include building scalable ML pipelines, managing large climate datasets, enabling reproducible experiments, and supporting model training and evaluation on high-performance computing and cloud infrastructure. The Researcher will work collaboratively with researchers and students within the FineCast project at the University of the Witwatersrand, and with partners across AfriClimate AI, African National Meteorological and Hydrological Services (NMHSs), and international research institutions. **What you will do** * Develop and maintain machine learning infrastructure and pipelines supporting the FineCast research programme. * Build scalable workflows for training, evaluating, and deploying AI-based weather and climate forecasting including generation, compression and archival of hindcasts from frontier models. * Manage and process large meteorological and climate datasets, including satellite data, reanalysis products, and observational station data. * Support the training and fine-tuning of global AI weather prediction models using regional datasets. * Implement systems for experiment tracking, reproducibility, and model versioning in machine learning research. * Develop tools and infrastructure supporting forecast verification and model benchmarking. * Support the integration of weather forecasting outputs with climate risk modelling and analytics workflows developed within the School’s research programme. * Contribute to the development of open-source software and research tools produced by the project. * Work closely with researchers and postgraduate students to translate research ideas into scalable and reliable machine learning systems. **Requirements (from the original advert)** * A Master’s degree or PhD in Computer Science, Machine Learning, Data Science, Software Engineering, Applied Mathematics, or a related field. * Strong programming skills in Python and experience with modern machine learning frameworks such as PyTorch, TensorFlow, or JAX. * Experience building and maintaining machine learning pipelines and data workflows. * Experience working with large-scale scientific or geospatial datasets. * Experience with high-performance computing environments, GPU clusters, or cloud platforms e.g., GCP, AWS, or similar. * Experience using version control systems e.g., Git and collaborative software development practices. * Ability to work effectively in interdisciplinary research teams. * Strong problem-solving skills and attention to reproducibility and reliability in scientific computing workflows. * Experience in one or more of the following areas will be advantageous: * MLOps and machine learning infrastructure * Distributed training of deep learning models * Geospatial data processing and climate datasets * Containerization technologies such as Docker and Kubernetes * Weather or climate modelling systems * Forecast verification or climate data analytics **Who should apply** This role is ideal for a candidate with an advanced degree (Master’s or PhD) in Computer Science, Machine Learning, Data Science, Software Engineering, Applied Mathematics, or a related field. The successful applicant should possess strong Python programming skills, experience with modern machine learning frameworks, and a background in building and maintaining ML pipelines and data workflows. Experience managing large-scale scientific or geospatial datasets, as well as working with high-performance computing or cloud environments, is essential. Candidates should be proficient in version control systems and collaborative software development, demonstrate strong problem-solving skills, and prioritize reproducibility and reliability in scientific computing. The role requires the ability to work effectively within interdisciplinary research teams and involves close collaboration with researchers and students on climate-focused AI projects. Individuals with advantageous experience in MLOps, distributed deep learning, geospatial data processing, containerization, weather/climate modelling, or forecast verification are encouraged to apply. **Deadline** 18th October, 2026 **Reference** Original posting: https://www.myjobmag.co.za/job/researcher-in-machine-learning-and-mlops-2-year-full-time-fixed-term-contract-university-of-the-witwatersrand Source: myjobmag

Summary drafted with AI assistance from the original advert. The advert itself is the authority — how we use AI.

At a glance

• Python
• AWS
• Google Cloud
• Docker
• Kubernetes
• Git

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