Location: Hybrid (Gauteng-Based)
Industry: AI, Machine Learning, Workforce Automation
Experience Level: Mid level
Salary: Market-Related Increase
Push the Boundaries of AI & NLP Innovation
We’re a global AI-driven powerhouse on a mission to revolutionise workforce management through smart automation and cutting-edge machine learning. Operating across the UK, USA, and Dubai, our AI solutions streamline complex processes, enhance compliance, and boost workforce efficiency.
We’re looking for a Machine Learning Engineer with NLP expertise to fine-tune, optimise, and scale advanced ML models—ensuring high performance, low latency, and seamless backend integration.
If you’re passionate about scalable, real-world AI deployment, LLM fine-tuning, and building high-performance NLP systems, this is your opportunity to work on production-ready AI—not just Proof-of-Concepts.
Responsibilities:
- Optimising & Scaling ML Models – Enhance performance, reduce latency, and streamline deployment pipelines.
- Fine-Tuning NLP Models – Drive accuracy and efficiency in text-based AI and document processing.
- Deploying AI in Kubernetes-Based Pipelines – Ensure scalability, reliability, and seamless integration into backend systems.
- Processing Structured & Unstructured Data – Work with OCR-based document classification & automation.
- Cloud-Based AI Operations – Build and deploy AI models in AWS, GCP, or Azure using Docker & Kubernetes.
- Collaborating with Backend Engineers – Integrate AI-driven solutions into scalable microservices architectures.
Minimum Requirements:
Machine Learning & AI Deployment:
- 5–6 years of hands-on AI/ML experience – working with real-world, scalable AI solutions.
- Strong NLP expertise – advanced text representation, semantic extraction, entity recognition.
- Fine-tuning LLMs – experience with smaller, optimised AI models for production environments.
- ML frameworks expertise – PyTorch (preferred), TensorFlow, or JAX.
- Knowledge of Model Compression – quantisation, inference acceleration.
Software Engineering & Infrastructure:
- Strong programming skills – Python, Java, etc.
- Cloud experience – Google Cloud (preferred), AWS or Azure acceptable.
- Containerisation & Orchestration – Docker, Kubernetes, CI/CD pipelines.
- Experience in microservices architecture – deploying scalable, cloud-based AI systems.
- Familiarity with Bash shell scripting – useful for automation.
NLP & Document Processing:
- Expertise in NLP libraries – NLTK, spaCy, Transformers.
- Experience with OCR & NLP-based document classification.
- Hands-on experience processing structured/unstructured text.
- Web scraping & document parsing (PDFs, DOCX) – a plus.
Nice to Have:
- Multi-threading/parallelisation experience.
- DeepSpeed, AWQ, PEFT – useful for optimising smaller models.
- LLM pipeline development & prompt engineering.
- Redis or similar caching/database experience.
Why Join Us?
- Build & deploy AI at scale – Work on production-ready AI systems, not just research prototypes.
- Be part of a global AI powerhouse – Collaborate with teams in the UK, USA, and Dubai.
- Work with state-of-the-art AI infrastructure – Leverage Google Cloud, AWS, Kubernetes, and ML frameworks.
- Competitive salary, career growth & cutting-edge AI projects.
Ready to Apply?
If you’re a Machine Learning Engineer passionate about NLP, AI scalability, and backend integration, we’d love to hear from you.
Send your CV to: natasha@skillzpage.com
Application Deadline: If you don’t hear back within two weeks, please consider your application unsuccessful.
