Location: Lisbon, Portugal
  Remote: Yes
  Willing to relocate: Maybe
  Technologies: Node.js, TypeScript/JavaScript, Express, Next.js, Zod, Supabase/PostgreSQL, Tailwind CSS, LangChain, React, Vue.js, GraphQL, gRPC, Go (learning)
  Résumé/CV: https://drive.google.com/file/d/10jfFaDlciDk8k44epHeYsGwWhKViOAqJ/view
  Email: ademilsonft@outlook.com
  LinkedIn: https://www.linkedin.com/in/ftonato
  GitHub: https://github.com/ftonato

  Location: Lisbon, Portugal
  Remote: Yes
  Willing to relocate: Maybe
  Technologies: Node.js, TypeScript/JavaScript, Express, Next.js, Zod, Supabase/PostgreSQL, Tailwind CSS, LangChain, React, Vue.js, GraphQL, gRPC
  Résumé/CV: https://drive.google.com/file/d/10jfFaDlciDk8k44epHeYsGwWhKViOAqJ/view
  Email: ademilsonft@outlook.com
  LinkedIn: https://www.linkedin.com/in/ftonato
  GitHub: https://github.com/ftonato

  Location: Lisbon, Portugal
  Remote: Yes
  Willing to relocate: Maybe
  Technologies: Node.js, TypeScript/JavaScript, Express, Next.js, Zod, Supabase/PostgreSQL, Tailwind CSS, LangChain, React, Vue.js, GraphQL, gRPC
  Résumé/CV: https://drive.google.com/file/d/1uTzDloINdkEwNBneTa9kLrkMCYLJw7-G/view
  Email: ademilsonft@outlook.com
  LinkedIn: https://www.linkedin.com/in/ftonato
  GitHub: https://github.com/ftonato

A common pattern I kept seeing is to split the problem into two stages:

1. Retrieve a small set of relevant candidates

2. Re-rank them using a model

Instead of doing brute-force inference across all items, I built a small prototype around this idea.

The flow looks like this:

- Store embeddings in a vector database (ChromaDB)

- Retrieve the Top-K most similar items/users based on vector similarity

- Run a TensorFlow.js model to re-rank the candidates

The goal is to reduce the search space before applying inference, which seems necessary when latency and scale matter.

What I found interesting is that once you move to this approach, a lot of the complexity shifts from the model itself to the retrieval layer:

- choosing K

- filtering candidates

- embedding quality

- latency vs recall trade-offs

Curious how others approach this in real systems:

- How do you decide on K?

- Do you rely purely on vector similarity or add heuristics?

- How do you handle re-ranking at scale?

Project: https://github.com/ftonato/recommendation-system-chromadb-tf...

Comments URL: https://news.ycombinator.com/item?id=47186896

Points: 2

# Comments: 0

  Location: Lisbon, Portugal
  Remote: Yes
  Willing to relocate: Maybe
  Technologies: Node.js, TypeScript/JavaScript, Express, Next.js, Zod, Supabase/PostgreSQL, Tailwind CSS, LangChain, React, Vue.js, GraphQL, gRPC
  Résumé/CV: https://drive.google.com/file/d/1ps9Aj0tS16z499GXEUsqxMZ2trTFblgf/view
  Email: ademilsonft@outlook.com
  LinkedIn: https://www.linkedin.com/in/ftonato
  GitHub: https://github.com/ftonato

  Location: Lisbon, Portugal
  Remote: Yes
  Willing to relocate: Maybe
  Technologies: Node.js, TypeScript/JavaScript, Express, Next.js, Zod, Supabase/PostgreSQL, Tailwind CSS, LangChain, React, Vue.js, GraphQL, gRPC
  Résumé/CV: https://drive.google.com/file/d/1ps9Aj0tS16z499GXEUsqxMZ2trTFblgf/view
  Email: ademilsonft@outlook.com
  LinkedIn: https://www.linkedin.com/in/ftonato
  GitHub: https://github.com/ftonato

Many companies advertise "remote" roles, but hiring is limited to the US, Canada, UK, or Germany. Sometimes they add one or two more countries, but rarely anything beyond that.

Given that it's the last quarter of 2025 and remote work is more established than ever, I'm trying to understand the reasoning behind this.

A few questions I'm hoping founders, hiring managers, or people with international hiring experience can shed light on:

- Is the main blocker regulatory complexity? (employment law, compliance, local registrations, PE risk, etc.)

- Is it primarily about taxes and payroll overhead when hiring abroad?

- Are there security or liability concerns that make certain jurisdictions easier to work with?

- Is it simply the cost of maintaining compliant employment structures worldwide, or are there deeper strategic reasons?

- And finally: Is there evidence that the value produced by strong engineers abroad doesn't offset those costs, or is the issue not economic at all?

I'm asking out of genuine curiosity, from the outside, it seems like a global talent pool should be an advantage, especially for remote-first companies. But the hiring restrictions persist, even as tools like Deel, Remote, Oyster, etc. mature.

I'd love to hear perspectives from people who have dealt with this firsthand.

Comments URL: https://news.ycombinator.com/item?id=46213671

Points: 26

# Comments: 19

Comments URL: https://news.ycombinator.com/item?id=36012087

Points: 1

# Comments: 1

Comments URL: https://news.ycombinator.com/item?id=35778142

Points: 1

# Comments: 1

Comments URL: https://news.ycombinator.com/item?id=35751951

Points: 1

# Comments: 1

On the docs page we have under the Acknowledgments session the first item that presents the License (MIT).

If it wasn't clear, I can move to a separate session :)

Comments URL: https://news.ycombinator.com/item?id=27493443

Points: 2

# Comments: 6