AI Engineer

Job Mail • Python • 1 hour ago
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≈ $22k – $56k per year (Estimated)
Location
In office
Seniority
Middle · 4+ years exp
Employment
Full-Time
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Job Mail

Job Mail is a South African online job board offering a large selection of vacancies across the country and some positions abroad. Job seekers can search and apply for jobs online, upload a CV and receive job alerts, while employers and recruitment agencies can advertise positions to a broad national audience. The brand is one of the longer-established names in South African job advertising and is operated from South Africa.
jobmail.co.za • HQ: Pretoria, South Africa • Job Boards & Aggregators
  • Design, build, and deploy machine learning and LLM-based systems, including retrieval-augmented generation (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.
  • Establish evaluation frameworks and metrics to measure model quality, drift, hallucination rate, and business impact over time.
  • Collaborate with full-stack engineers to expose AI capabilities through clean, well-documented APIs and SDKs.
  • Implement guardrails, safety checks, and monitoring for AI systems running in production.
  • Stay current with the fast-moving AI/ML landscape and bring back practical recommendations on tools, models, and techniques.
  • Write clear technical documentation and communicate trade-offs to both technical and non-technical stakeholders.
Required Experience
  • 4+ years of experience building and shipping machine learning or AI-powered systems in production.
  • Strong Python skills, with hands-on experience using frameworks such as PyTorch, TensorFlow, or similar.
  • Practical experience with large language models - prompting, fine-tuning, RAG, or agent frameworks (e.g., LangChain, LlamaIndex, or custom implementations).
  • Hands-on experience training and fine-tuning open-source models (e.g., Llama, Mistral, Qwen) - full fine-tuning or parameter-efficient methods (LoRA/QLoRA) - and deploying them on your own infrastructure rather than relying solely on hosted APIs.
  • Experience standing up self-hosted inference serving on your own infra (e.g., vLLM, TGI, Triton, Ray Serve), including GPU provisioning, batching, and cost/latency optimization.
  • Solid understanding of ML fundamentals: model evaluation, overfitting, data leakage, and experimentation methodology.
  • Experience with vector databases and embedding-based retrieval (e.g., Pinecone, Weaviate, pgvector, FAISS).
  • Comfort working with cloud infrastructure (AWS, GCP, or Azure) and containerized deployments (Docker, Kubernetes), including GPU-backed compute.
  • Familiarity with MLOps practices - model versioning, CI/CD for ML, monitoring, and rollback strategies for both hosted and self-hosted models.
  • Strong software engineering fundamentals: clean code, testing, code review, and API design.
  • Proficiency working with AI coding assistants (e.g., Claude Code, GitHub Copilot, Cursor) to accelerate development, while critically reviewing and validating AI-generated code.
  • Excellent communication skills and comfort working in a remote, async-friendly environment.
Nice to Have
  • Experience with model quantization, distillation, or optimization techniques (e.g., GPTQ, AWQ, ONNX) for efficient self-hosted inference.
  • Background in NLP, computer vision, or recommendation systems.
  • Experience with streaming data pipelines (Kafka, Spark) or feature stores.
  • Contributions to open-source ML/AI tooling.
  • Prior experience in a startup or fast-growth environment.
Please note that only shortlisted candidates will be contacted.
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