Data Scientist â Machine Learning & Generative AI
Network Recruitment Johannesburg
Data Scientist Machine Learning & Generative AI
What Youll Work On:
- Building Large Language Model (LLM) solutions (GPT, LLaMA, Mistral, Claude, and Falconbut tuned for real-world business impact).
- Training and fine-tuning transformer architectures (BERT, T5, GPT-3/4, etc.) on domain-specific datasets.
- Designing speech-to-text pipelines (Whisper, wav2vec, and Hugging Face speech models).
- Creating conversational AI systems that actually talk and thinkbeyond simple FAQ chatbots.
- Developing retrieval-augmented generation (RAG) pipelines with vector databases (Pinecone, Weaviate, FAISS, and Milvus).
- Owning the end-to-end ML lifecycle: Data wrangling, training, evaluation, and deployment (Docker, Kubernetes, AWS/Azure/GCP).
What Were Looking For:
- 26 years experience in data science / ML (MSc or PhD preferred in AI, CS, Data Science, Applied Mathematics, or similar).
- Strong grounding in deep learning & NLP (transformers, embeddings, and attention mechanisms).
- Hands-on experience fine-tuning or deploying LLMs and transcription models.
- Solid coding skills in Python, with experience in PyTorch, TensorFlow, and Hugging Face.
- Exposure to MLOps, deployment pipelines, and cloud platforms.
- A true problem-solver and innovatorSomeone who loves building new things, not just wrapping tools together.
Why Join?:
- Be part of a team solving real problems with cutting-edge AI.
- Work in an environment that values experimentation, bold ideas, and real impact.
- Build systems that will be used every daynot just prototypes that collect dust.
- Hybrid setup with flexibility and growth opportunities.
This is your chance to push the boundaries of Generative AI and leave your fingerprint on solutions that change how people interact with technology.
Apply directly to
Network RecruitmentJohannesburg
Key Responsibilities:
• Build, fine-tune, and deploy Large Language Models (LLMs) across domains.
• Develop and implement chatbots, transcription systems, and RAG pipelines.
• Design and optimise end-to-end ML lifecycles, from data preprocessing to...
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