DATA SCIENCE / AI / ML ENGINEERING

Zaheeda Chauke

8+ Years Experience

Data Scientist and AI/ML Engineer focused on production-oriented machine learning, MLOps, LLM applications and reliable model delivery.

Explore my work Download CV ↓

BSc Applied Mathematics & Computer Science UNISA

Data Science Analytics & Insights

End-to-End MLOps production-oriented systems

AI LLM & applied ML

01 / FEATURED PROJECTS

Featured Projects

Selected engineering projects spanning MLOps, LLM applications, evaluation, CI/CD and model fine-tuning.

END-TO-END ML SYSTEM 01

From model training to production.

End-to-end MLOps system covering feature management, experiment tracking, validation, model registration, production serving, monitoring and automated retraining.

Python

MLflow

Feast

BentoML

Docker

Airflow

Kubernetes

View repository ↗

LLM / GRAPHRAG 02

Agentic RAG chatbot for internal hospital knowledge retrieval.

LLM application using LangChain, Neo4j GraphRAG, vector retrieval, FastAPI and Streamlit across synthetic hospital data.

Python

LangChain

Neo4j

FastAPI

Streamlit

View repository ↗

CI / CD 03

Automating the ML delivery lifecycle.

GitHub Actions pipeline automating model training, evaluation and reporting with CML, followed by deployment to Hugging Face Hub.

GitHub Actions

CML

Scikit-learn

Hugging Face

View repository ↗

RAG / EVALUATION 04

Making LLM quality measurable.

Evaluation framework for RAG applications with MLflow tracking and automated evaluation workflows for reproducible assessment.

Python

MLflow RAG RAG LLM LLM Evaluation

View repository ↗

GENERATIVE AI 05

Fine-tuning an LLM for specialised dialogue.

Fine-tuned Meta Llama 3 on a medical dialogue dataset using PEFT and LoRA, then merged, quantized and prepared the model for local inference with llama.cpp.

Python

PyTorch

Hugging Face LoRA PEFT / LoRA GGUF GGUF

View repository ↗

02 / TECHNICAL SKILLS

Technical Skills

The tools and engineering disciplines I use to build, deploy and evaluate machine-learning systems.

01 PROGRAMMING

Programming

Languages, data manipulation and development environments used across data science and engineering.

Python SQL SQL

PostgreSQL

Pandas

Scikit-learn

PySpark C++ C++ R R

Git

Linux

Jupyter

02 MLOPS

MLOps & ML Engineering

End-to-end ML pipelines, deployment, experiment tracking, registries, feature stores, monitoring, drift detection and automated retraining.

MLflow

Feast

BentoML E Evidently

Airflow

GitHub Actions

Kubeflow TFX TFX MLMD ML Metadata D DagsHub H Hopsworks

03 INFRASTRUCTURE

Cloud, Containers & Infrastructure

Containerisation, orchestration, cloud infrastructure and infrastructure-as-code.

Docker

Kubernetes YAML YAML

Terraform

AWS

GCP AZ Azure OpenAI

04 GENERATIVE AI

Generative AI

LLM applications, retrieval systems, prompting, evaluation and human feedback workflows.

AI LLMs

LangChain RAG RAG G GraphRAG P Prompt Engineering HF Human Feedback RLHF RLHF / HITL

05 MACHINE LEARNING

Machine Learning & AI

Classical machine learning, deep learning, NLP, computer vision and model evaluation.

Scikit-learn

TensorFlow

PyTorch CV Computer Vision NLP NLP CNN CNNs RNN RNNs / LSTMs T Transformers

06 DATA & STORAGE

Data & Storage

Relational, document and graph databases used for analytics and AI applications.

SQL SQL

PostgreSQL

MongoDB

Neo4j

07 STATISTICS

Statistics

Statistical reasoning supporting experimentation, model evaluation and decision-making.

P Probability D Distributions H Hypothesis Testing A/B A/B Testing B Bayesian Models

03 / EXPERIENCE

Experience

Data science, machine learning and AI engineering across consulting, production work and applied research.

OUTLIER.AI

Code Expert / Freelancer

2024 — PRESENT

LLM training and fine-tuning, prompt generation, RLHF and human-in-the-loop evaluation, alongside Python and C++ code review, debugging, refactoring and performance optimisation.

LLMs RLHF Python C++

ZELO ANALYTICS

Data Scientist & ML Engineer

2021 — 2023

Built end-to-end analytics, machine-learning and AI solutions including segmentation, churn, recommendation, LLM/GraphRAG, CI/CD, MLOps, cloud infrastructure and monitoring.

MLOps Cloud AI GraphRAG

OMDENA · AI FOR GOOD

Machine Learning Engineer

2021 — 2022

Credit scoring team lead and contributor across NLP projects including environmental conflict tracking and coreference resolution.

Machine Learning NLP Team Lead

THE GRADIENT BOOST

Data Science Mentor

2020 — 2021

Mentored learners in Python, SQL, Pandas, descriptive statistics, visualisation and machine learning, with emphasis on communication and practical problem solving.

Python SQL Machine Learning

TELKOM INSIGHTS

Data Scientist — AI & Insights

2018 — 2019

Worked across churn propensity, customer segmentation, conversational AI, speech-to-text, COVID-19 analytics, computer vision and NLP.

Python NLP Computer Vision Dialogflow

EXPLORE SOFTWARE / BCX

Data Science Intern

2018 — 2019

Worked with SQL databases, data quality, exploratory analysis, Python visualisation modules and introductory deep-learning workflows.

Python SQL EDA

Contact

Contact me

I'm open to full-time remote or on-site work in South Africa.

Email me ↗ GitHub ↗ Medium ↗