temporary position- machine learning(ml)/data engineer

2 weeks ago

Nairobi, Nairobi Area, Kenya African Population and Health Research Center (APHRC) Full time $90,000 - $120,000 per year


Machine Learning/Data Engineer,

Key Responsibilities
  • Integrate and deploy AI/ML models and LLMs within mobile and web applications.
  • Develop, manage, and optimize Dockerized AI services.
  • Ensure high availability, scalability, and security across cloud and on-prem systems.
  • Automate and streamline CI/CD pipelines to facilitate seamless updates.
  • Implement cost-monitoring and optimization strategies for cloud resources.
  • Develop comprehensive disaster recovery plans for critical AI services.
  • Maintain secure and efficient API interactions with AI models.
  • Monitor, measure, and enhance API latency for real-time responsiveness.
  • Document AI workflows and data pipelines to facilitate cross-team collaboration.

Education Qualifications, Experience And Core Competencies
  • Bachelor's degree in computer science, Data Science, or a related field with specialization in AI/ML.
  • Two (2) years of experience in DevOps/cloud roles, including at least one (1) year specifically dedicated to AI model deployment.
  • Hands-on experience integrating ML models (TensorFlow Lite, ONNX, PyTorch) into mobile applications.
  • Proficiency with Large Language Model (LLM) APIs such as OpenAI, DeepSeek, Claude, and Llama, including advanced prompt engineering techniques.
  • Experience in building Retrieval-Augmented Generation (RAG) pipelines, fine-tuning, and developing agent-based systems.
  • Strong familiarity with AI orchestration frameworks like LangChain, LlamaIndex, or AutoGen.
  • Knowledge and practical experience with vector databases (FAISS, Chroma, Pinecone, Weaviate).
  • Proficiency in Python data transformation tools, including pandas, NumPy, scikit-learn, and pyCaret.
  • Familiarity with ML model deployment tools (MLflow, Seldon Core).
  • Expertise with containerization technologies (Docker) and orchestration platforms (Kubernetes—EKS, GKE, AKS).
  • Mastery of cloud services on AWS, GCP, Azure, or on-prem equivalents such as OpenStack.
  • Strong experience in Infrastructure as Code (IaC) tools like Terraform, Ansible, or Pulumi.
  • Proficient in setting up CI/CD pipelines using GitHub Actions, ArgoCD, or Jenkins.
  • Familiarity with monitoring and logging solutions such as Prometheus, Grafana, and ELK Stack.
  • Knowledge of model quantization and edge AI for efficient on-device inference.
  • Experience with model serving platforms like TensorFlow Serving or Triton Inference Server.
  • Competency in database scaling and management, specifically PostgreSQL/MySQL for AI workloads.
  • Strong analytical skills to troubleshoot and solve deployment bottlenecks.
  • Ability to manage and optimize cloud/on-prem infrastructure costs.
  • Security-focused mindset to ensure robust, secure AI application deployments.
  • Proven capability in designing scalable and efficient AI architectures.
  • Excellent documentation and knowledge-sharing abilities.
  • Excellent teamwork and communication skills.

July 04, 2025

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