Data Scientist (AI & ML)

Recruiter:

Network Recruitment

Job Ref:

NFP016120/MNG

Date posted:

Monday, September 29, 2025

Location:

Johannesburg, South Africa

SUMMARY:
Are you ready to shape the future of Generative AI? This is your opportunity to join a visionary team where your mastery in AI, data engineering, and machine learning isn’t just valued, it’s mission-critical. If you’re passionate about building and deploying GenAI solutions that redefine how businesses operate, then this role was built for you.

POSITION INFO:
Our client is a leading, innovative, and driven organization, pioneering advanced AI capabilities across their ecosystem. They are searching for a Data Scientist – Generative AI to drive end-to end AI initiatives, from LLM development and RAG frameworks to scalable deployment and data pipeline engineering. This isn’t support work, it’s transformation at an enterprise level.

Key Responsibilities:

Design, develop, and optimize Generative AI models for operational and analytical use
Build and fine-tune RAG frameworks using tools like LangChain, LlamaIndex, and other LLM platforms
Engineer scalable data pipelines and perform ETL to support AI model training and deployment
Collaborate with data and DevOps teams to deploy AI solutions in production environments
Integrate data from multiple sources and ensure robust data warehousing and accessibility
Drive performance, scalability, and cost efficiency for AI models in cloud and on-prem settings
Communicate complex AI concepts to non-technical stakeholders and align work to business goals
Continuously research, experiment, and stay ahead of GenAI trends and architectures

Job Experience and Skills Required:

3+ years in AI/ML, with at least 1–2 years focused on Generative AI
Strong background in data engineering, ETL processes, and pipeline development
Hands-on experience with TensorFlow, PyTorch, and GenAI frameworks
Proficiency in Python, SQL, Pandas, and NumPy
Experience with cloud platforms (AWS, GCP, and Azure) and container tools (Docker and Kubernetes)
Knowledge of MLOps practices, including model versioning, monitoring, and retraining
Familiarity with big data and storage tools like Spark, Hadoop, and vector databases
Excellent communication, teamwork, innovation mindset, and analytical problem-solving
Bachelor’s Degree in Computer Science, Data Science, ML, or a related field (Master’s/PhD advantageous)
Preferred Certifications:
- AWS Certified Machine Learning / AI Practitioner
- GCP ML Engineer or Cloud Engineer
- Microsoft Azure AI Engineer / Data Science

Apply now!

For more exciting AI, Data Science, and Analytics opportunities, visit:
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I also recruit across:

AI & Machine Learning
Data Engineering
Actuarial & Analytics
Product & Model Development
Pricing & Valuations
Risk & Automation

If you haven’t heard back in two weeks, please consider your application unsuccessful. Your profile will be retained for future opportunities.

For more information, contact:
Kholo Mongalo
Recruitment Researcher in Actuarial & Analytics
Connect with me on LinkedIn:

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