Dimitre Oliveira Portfolio
Kaggle Grandmaster and Google Developer Expert (ML) working as an ML engineer at Intuition Machines; notebooks and GitHub span TensorFlow/Keras production pipelines through to modern generative AI (Gemini, Vertex AI, Stable Diffusion fine-tuning) apps.
What makes it work
A breakdown of the choices that make this portfolio stand out.
Google Developer Expert status as third-party validation
GDE status is awarded by Google based on community contribution and depth, independent of any employer — a second institution vouching for the same skill set as his Kaggle rank.
Demonstrated range from classic deep learning to current GenAI
Shipping projects across TensorFlow/Keras and newer Gemini/Vertex AI/Stable Diffusion work shows the portfolio is actively maintained, not stuck on 2019-era tutorials.
Full small-app builds, not just model notebooks
Building and shipping small end-to-end apps (a Streamlit PaLM app, a deployed generative Hangman game) proves he can wrap and ship a model, closer to the real ML engineer job.
What ML Engineers can take from this
Specific, actionable tips to apply to your own portfolio — no generic advice.
Pursue independent technical recognition (GDE, MVP, etc.) alongside competition results.
Keep at least one recent project on this year's frontier stack so the portfolio does not read as frozen.
Ship the model behind a real interface at least once — deployment beats a bare notebook.
Write a short post on the deployment decisions for every project, not just the modeling choices.
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