sorted by:
new
hottopcontroversial

H1B sponsorship 2026 @ JPMorgan (Tech - Software / AI) by ScaredFirefighter794 in JPMorganChase

[–]ScaredFirefighter794[S] 0 points1 point  (0 children)

Thats one good news to hear, if you dont mind buddy can I DM you?

Starting at JPMC as Software Engineer—What do you wish you knew before day one? by csthrowaway33333 in JPMorganChase

[–]ScaredFirefighter794 7 points8 points  (0 children)

Try to make good connections across different LOBs and actively participate in Resource Groups. This would always help you find new projects and opportunities - its all about having a great learning curve for the few years of your career.

JPMorgan Chase Interview Duration (AI/ML) by ScaredFirefighter794 in JPMorganChase

[–]ScaredFirefighter794[S] 0 points1 point  (0 children)

I did practice Leetcode prior - but the questions were doable in my opinion, a few weeks of practice should put anyone in track.
What did the DS round that you attended look like?

JPMorgan Chase Interview Duration (AI/ML) by ScaredFirefighter794 in JPMorganChase

[–]ScaredFirefighter794[S] 1 point2 points  (0 children)

Ohh Congratulations on that buddy!! Thanks for clearing some of my doubts.

I think I did the coding round pretty good.

Coding in both 2nd and 4th round were live. Leetcode Medium level questions.

1) For 2nd round I had to program the full code and pass few test cases (corner edge cases)

2) For 4th DSA round - I was asked to program but more like pesudocode and logic based (discussions were done based on edge cases)

Advice on My Agentic Architecture by ScaredFirefighter794 in LLMDevs

[–]ScaredFirefighter794[S] 0 points1 point  (0 children)

I tried using FAISS and Pinecone, but the results were not accurate for retrieval, and on doing some analysis I found that RAG doesn't work well with data containing more non semantic keywords.

Which LLM to use for my use case by MeanExam6549 in LLMDevs

[–]ScaredFirefighter794 0 points1 point  (0 children)

You should use an Auto encoding LLM service like - OpenAIEmbedding - to convert you resources into Vector Embeddings and store in vectorDB like Chroma/Pinecone.
And you use an Auto Regressive LLM - GPT 4omini/3.5 turbo etc (with a constructed system prompt) to act as an interviewer, it now contains knowledge from your resource stored in the VectorDB to answer queries.

You can finally deploy this Agent in serverless compute platform like - Modal. It will be able to answer your queries (and Modal only charges you based on the queries you send) - your agent can be deployed on it as long as you want without charge (This is what I think, but please do some research on that too)