Noemdek's advisory practice was established to support international strategic advisory firms with relevant local expertise. We are able to deliver on our promise to our partners because we have a strong team of people trained at some of the world's top universities who have immersed themselves in the Nigerian business community. In addition to partnering with international advisory firms, Noemdek also works directly with clients in the healthcare, financial services, consumer goods and oil and gas industries. Similar to our venture capital business, we are fully committed to helping our clients with solutions that will ensure they have a lasting competitive advantage. Therefore, we look beyond standard solutions to develop effective partnership structures, new insights, mobilize organizations, drive tangible results, and make public and private institutions more capable. Our customized approach combines deep insight into the dynamics of companies and markets with close collaboration at all levels of the client organization. This ensures that our clients build more capable organizations, and secure lasting results. We seek to be agents of change-for our clients, our people, and society overall. Noemdek also leverages its relationships with investors to support clients in raising capital to fund acquisitions.
As our AI Engineer, you will own the design, development, and deployment of AI models within our applications. You will work closely with the team to transform business requirements into production-ready AI solutions, leveraging both custom models and third-party APIs. You’ll also be responsible for setting up and managing robust MLOps pipelines to ensure continuous improvement and scalability of AI systems.
Key Responsibilities:
- Build, fine-tune, and deploy AI/ML models (NLP, CV, LLMs, or domain-specific).
- Integrate AI into existing and new application backends.
- Develop and maintain MLOps pipelines for training, deployment, and monitoring.
- Optimize AI features for latency, scalability, and cost-efficiency.
- Collaborate with data specialists and product team to ensure models are trained on high-quality datasets.
- Track model performance and iterate based on feedback and metrics.
Requirements:
- Proven experience as an ML Engineer or AI Engineer, with production-level deployments.
- Strong proficiency in Python and ML frameworks (TensorFlow, PyTorch, Hugging Face).
- Experience with LLMs (fine-tuning, prompt engineering, embeddings).
- Familiarity with MLOps tools (MLflow, Kubeflow, AWS Sagemaker, Azure ML, GCP Vertex AI).
- Experience integrating AI into APIs or full-stack applications.
- Strong understanding of cloud environments and containerization (Docker, Kubernetes).
- Experience with vector databases (Pinecone, Weaviate, Milvus).
- Experience with reinforcement learning or multi-modal AI models
Method of Application
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