Remote AI Engineer: Build Scalable ML & LLM Systems

e-Merge IT Recruitment; South Africa; Remote; ZAR 480,000 - 800,000; Full time

Job summary

E-Merge is seeking an AI Engineer who can bridge research and production, prototyping fast and shipping reliable, cost-efficient AI features at scale. You’ll work with product and full-stack engineering to convert ambiguous problems into tangible improvements.

You’ll design and deploy ML and LLM-based systems, manage data pipelines, and optimize for latency and cost, with a focus on open-source and self-hosted solutions in a cloud and containerized environment.

Qualifications

• 4+ years of experience building and shipping ML/AI powered systems in production.
• Strong Python skills with PyTorch/TensorFlow or similar.
• Hands-on experience with large language models - prompting, fine-tuning, RAG, or agent frameworks.

Responsibilities

• Design, build, and deploy ML and LLM-based systems, including RAG pipelines, fine-tuned models, and agentic workflows.
• Own the full lifecycle of AI features: data collection and evaluation, model/prompt selection, experimentation, deployment, and monitoring in production.
• Build and maintain data pipelines, embeddings stores, and vector databases that support search, retrieval, and personalization.
• Evaluate and integrate third-party model APIs (OpenAI, Anthropic, etc.) alongside open-source and self-hosted models, balancing quality, latency, and cost.
• Fine-tune, train, and deploy open-source models on our own infrastructure - including data prep, training/fine-tuning runs, quantization, and self-hosted inference serving at scale.
• Stay current with the fast-moving AI/ML landscape and bring back practical recommendations on tools, models, and techniques.

Job description

E-Merge is seeking an AI Engineer who can bridge research and production, prototyping fast and shipping reliable, cost-efficient AI features at scale. You’ll work with product and full-stack engineering to convert ambiguous problems into tangible improvements.

You’ll design and deploy ML and LLM-based systems, manage data pipelines, and optimize for latency and cost, with a focus on open-source and self-hosted solutions in a cloud and containerized environment.