Senior Machine Learning Engineer / AI Specialist

About the role

The United Nations Volunteers – East and Southern Africa is seeking a Senior Machine Learning Engineer / AI Specialist to join its AI Programme in Nairobi, Kenya. The role will lead the data, modelling and evaluation layer for priority AI‑enabled solutions, working closely with the Ministry of Information, Communications and the Digital Economy and the Technopolis Development Authority.

Key responsibilities

• Assess data readiness, quality, coverage, labeling, provenance and licensing for selected AI use cases.
• Define training, validation and testing strategies and select appropriate modelling approaches across ML, NLP, computer vision, generative AI, large language models and retrieval‑augmented methods.
• Develop, adapt and fine‑tune models for five priority AI use cases and build data preparation, feature engineering, prompt engineering and retrieval pipelines.
• Lead structured experimentation, including hyper‑parameter searches, ablation studies and prompt configuration testing.
• Optimize model accuracy, size, latency and inference cost on on‑premise NVIDIA GPU compute resources.
• Create evaluation protocols, benchmark performance against baselines and conduct failure‑mode analysis.
• Collaborate with the Responsible AI Specialist to assess bias, fairness, robustness and privacy.
• Mentor junior AI developers, conduct code reviews and produce model cards, dataset documentation and hand‑over materials.

Required profile

• Minimum five years of progressive professional experience in machine learning, applied AI and data science.
• Proven experience delivering AI solutions in areas such as NLP, computer vision, generative AI or large language models.
• Hands‑on experience with on‑premise GPU environments, particularly NVIDIA hardware.
• Ability to design and execute rigorous model evaluation and bias‑assessment processes.
• Experience mentoring technical staff and documenting AI artefacts.

Required skills

• Machine learning
• Natural Language Processing (NLP)
• Computer vision
• Generative AI
• Large language models
• Retrieval‑augmented approaches
• Prompt engineering
• Hyper‑parameter tuning
• Model evaluation and benchmarking
• Bias and fairness assessment
• Data preparation and feature engineering
• NVIDIA GPU compute