Danial Azam
Sydney, New South Wales, Australia
Summary
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SeniorDanial Azam is a Senior Machine Learning Engineer with 9+ years delivering production ML, data and GenAI systems, currently driving platform engineering at wiqLabs (Woolworths Group) to productionize GenAI with Pulumi on GCP and GitHub Actions. He has deep experience deploying ML pipelines with Vertex AI, Kubeflow, BigQuery and Airflow, and builds repeatable MLOps design patterns for feature engineering, data prep and model deployment. Earlier research roles at the University of Sydney combined Bayesian inference, MCMC and surrogate modeling to accelerate geophysical simulations, reflecting a strong grounding in probabilistic methods and scientific software. Comfortable bridging research and production, he pairs hands-on cloud infrastructure work with algorithmic rigor and a track record of reducing simulation time without sacrificing accuracy. Based in Sydney, he brings a practical focus on developer self-service and scalable templates that shorten time-to-value for enterprise AI.
10 years of coding experience
Github Skills (25)
jekyll7
java7
database7
member6
oracle6
sql6
ai6
sqlite6
postgresql6
mysql6
jdbc5
db25
snowflake5
nosql5
databricks4
Programming languages (8)
Github contributions (5)
intelligentEarth/Bayeslands
Oct 2017 - Jun 2019
Contributions:79 commits, 78 pushes, 1 branch in 1 year 8 months
basin-genesis-hub/bgh_atlas
Jul 2019 - Nov 2020
Atlas jekyll 2
Contributions:160 commits, 142 pushes, 1 branch in 1 year 4 months
jekyll
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