Machine Learning Engineer building production AI systems across LLMs, computer vision, image generation, and scalable ML infrastructure.
I am a Machine Learning Engineer with 3+ years of experience building and scaling AI products across LLMs, semantic search, image generation, and real-time vision systems. My work has spanned high-traffic consumer apps, production inference infrastructure, healthcare-focused motion tracking, and retrieval-powered product discovery.
I have completed a Master of Artificial Intelligence and Machine Learning at the University of Adelaide, and previously earned a Bachelor of Computer Science from FAST-NUCES.
- Production LLM applications with retrieval, ranking, prompt workflows, and evaluation loops
- Search and recommendation systems powered by embeddings, vector search, and product normalization
- Scalable inference platforms for image generation and multimodal AI workloads
- Real-time computer vision systems for mobile and cross-platform applications
- Backend services and ML APIs designed for reliability, observability, and fast iteration
- Improved product search relevance by roughly 35-45% by building vector-based search with Elasticsearch and transformer embeddings.
- Built a RAG-powered recipe workflow that maps natural-language meal requests to recipes and semantically matched supermarket products.
- Shipped large-scale image generation infrastructure at Vyro for apps serving millions of users, including systems handling peaks of 20M requests per day with 99.5% uptime.
- Reduced avatar generation turnaround from hours to 15 minutes by implementing a Docker-based serverless training and inference pipeline on AWS and Runpod.
- Cut mobile pose estimation latency by 40% by optimizing MediaPipe-based body tracking for real-time deployment.
- Designed CI pipelines with GitHub Actions that pushed test coverage to 97% and substantially reduced production issues.
| Languages |
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| AI / ML |
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| LLM / GenAI |
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| Data / Retrieval |
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| Backend / Infra |
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| Cloud / Platforms |
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I am most interested in Machine Learning Engineer, Applied AI Engineer, and LLM Engineer roles where I can work on production AI systems, search and retrieval, multimodal products, and scalable ML infrastructure.