Technical Skills
Machine Learning Engineer with expertise across the full ML stack
Technical Overview 🔮
T-shaped expertise in machine learning with deep focus on Natural Language Processing and LLMs. Proven experience across major ML modalities (vision, audio, tabular, text) with strong software engineering and cloud infrastructure skills. Experienced in building production-ready ML systems at scale.
8+
Years Python
3
Cloud Platforms
4
ML Modalities
8+
Years Experience
Core Competencies ✨
Machine Learning & AI 🤖
Analytical Machine Learning
Natural Language Processing (NLP)
Structured/Tabular Prediction
Information Extraction
PII Detection/Masking
Search & Retrieval
Generative AI
Large Language Models (LLMs)
RAG Architectures
Text Generation
Content Synthesis
Speech & Audio
Automatic Speech Recognition (ASR)
Text-to-Speech (TTS)
Audio Processing
Speaker Diarization
Computer Vision
Optical Character Recognition (OCR)
Image Segmentation
Software Engineering 🔮
Programming Languages
Python (8+ years)
JavaScript/TypeScript
HTML, CSS
Backend Development
FastAPI
Flask
Async Processing (Celery, Redis)
REST APIs
Data & ML Libraries
pandas, numpy, scipy
scikit-learn, transformers
PyTorch, TensorFlow
Streamlit, Dash, Gradio
Performance & Scale
Accelerated Computing (GPUs, CUDA)
Distributed Computing
Multi-threading/Processing
Data Engineering ✨
Databases
PostgreSQL
Elasticsearch
MongoDB
Databricks
Data Processing
ETL Processes
Apache Spark
Large-scale Data Migrations
Monitoring & Governance
Monitoring Systems
Controls and Governance
Quality Assurance
Cloud & DevOps ☁️
Cloud Platforms
Azure
Google Cloud Platform
AWS
Infrastructure
Infrastructure as Code (Terraform)
Containerisation (Docker)
Container Orchestration (Kubernetes, Docker Swarm)
Load Balancing (Traefik, Nginx)
DevOps & CI/CD
Azure DevOps
GitLab CI/CD
GitHub Actions
Linux System Administration
Monitoring & Observability
Prometheus, Grafana
Logging & Tracing
Monitoring Systems
Key Strengths 🌙
🔮
Enterprise Architecture
Building scalable, maintainable ML platforms in regulated environments
✨
Full-Stack ML
End-to-end development from model training to production deployment
🌈
Cloud-Native
Deep expertise in Azure, GCP, and AWS with infrastructure as code
🔬
Research to Production
Translating cutting-edge research into practical enterprise solutions
Education 🎓
Bachelor's Degree in Computer Science
QUT, 2018
Dual minors in Psychology and Data-centric Computing. Graduated with distinction (6.214 GPA).