Data Engineer

Vicki Boykis Portfolio

Technical blog spanning 2015–2026 by ML/data infrastructure engineer Vicki Boykis, documenting real shipped projects like Viberary (a book recommendation system) and posts on operating embeddings and vector search at scale, including "Querying 3 billion vectors."

Data InfrastructureEmbeddingsVector SearchML Systems

What makes it work

A breakdown of the choices that make this portfolio stand out.

1

A named side project with a public retrospective

Viberary isn't just mentioned once at launch — a later retrospective post evaluates how the project actually performed, which is far more instructive than a typical "I built X" announcement post.

2

Concrete, quantified engineering problems as post titles

"Querying 3 billion vectors" and "How big are our embeddings now and why?" name the actual scale and question being solved, giving readers immediate context for the technical depth ahead rather than a vague thematic title.

3

A blog that documents production tradeoffs, not just successes

Writing about local model execution and infrastructure choices in practical, cost-and-tradeoff terms rather than purely celebratory terms reflects a working engineer's actual day-to-day decisions.

What Data Engineers can take from this

Specific, actionable tips to apply to your own portfolio — no generic advice.

  • If you ship a side project, write a retrospective months later on how it actually performed — that's more valuable to readers than the launch post alone.

  • Put the concrete scale or specific question in your post title ("querying 3 billion vectors") instead of a generic theme — it signals real depth immediately.

  • Write honestly about tradeoffs and things that didn't work as expected, not only clean success stories — it reads as more credible.

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