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mentorship

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Where to start, by what you're trying to do.

182 questions, guides, and concept notes can be a lot. Pick the path that matches why you're here. Each item links directly; come back to this page when you finish a path.

The three sections

1. Preparing for a senior ML interview loop

You have a loop in 2-8 weeks. You want to know what's actually tested at L5/L6 vs. what showed up on your old prep material.

  1. The 5 things AS interviews test for
  2. L5 vs L6 calibration: what's the difference
  3. Tell me about your most ambitious project
  4. How would you evaluate an LLM application
  5. Reduce LLM inference cost 10x
  6. Browse all 50 questions

2. Shipping LLM products or building agents

You're building a real LLM application or agent system. mlmentorship is interview-focused; my opinion writing on applied LLMs and agents lives on my personal site.

  1. Browse essays at hsaghir.com/blog (verification asymmetry, similarity-is-all-you-need, the-loop-is-the-product, under-specified coding agents).
  2. Skim Looplet, my iterator-first agent framework.
  3. For consulting on agents/evals/post-training: hsaghir.com/work-together.

3. PhD or postdoc transitioning to industry

You have research credentials. You want to know what industry interviews look like and how research projects translate to "ambitious project" stories.

  1. Applied Scientist vs MLE vs Research Engineer
  2. The 5 things AS interviews test for
  3. Tell me about your most ambitious project
  4. When you disagreed with a senior person
  5. Scoping an ambiguous problem

4. Building deep technical foundations

You want the canonical ML/DL reference, organized so you can study for breadth and depth in parallel.

  1. Foundations: matrices as linear maps → SVD and PCA → eigenvalues
  2. Probability: MLE → KL divergence → Bayes rule
  3. Deep learning: backprop → attention → transformers
  4. LLM internals: FlashAttention → KV cache → speculative decoding
  5. Browse all 124 concepts by sub-category

5. Engineering leader / hiring manager

You're not preparing for an interview. You want to calibrate what good looks like, what to test for, or who to hire.

  1. What senior ML interviews actually test
  2. L5 vs L6 calibration
  3. AS vs MLE vs Research Engineer (which role to hire)
  4. Why your team's eval pipeline is probably broken
  5. If you'd like a senior sounding board on a specific decision

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