Most senior engineers I meet know the rules. Very few know the machine underneath. That gap is what I help close, 1:1.
Here's a taste of the questions we go deep on:
1. Python.
class A:
def f(self): pass
a = A()
print(a.f is a.f) # False
print(a.f == a.f) # True
The same method, on the same object, is not itself. Why?
2. ML: Attention divides by √d_k before the softmax. Why the square root? What breaks if you divide by d_k instead?
3. LLMs: Without positional encodings, a transformer can't tell "dog bites man" from "man bites dog." What property of attention causes that?
If you couldn't fully explain all three, you're not behind. You're exactly who I enjoy working with.
Why this matters now: vibe coding feels like 10x until it breaks in prod and the model isn't on call. You are. AI multiplies understanding, and 10x of zero is still zero.
Who I am: I did ML research at MIT under Prof. John Tsitsiklis, worked as a software engineer, and I'm in the top 0.2% on LeetCode. For two years I've mentored senior engineers, tech leads, architects and PMs with 10 to 15+ years of experience, mostly in the US, some at the biggest firms in tech.
How I teach: No tutorials. Mental model → internals → edge cases. If your answer is almost right but conceptually wrong, I'll find the exact crack. The goal is that you could re-derive it yourself.
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Timezone / availability: Based in the US(PDT), and I travel regularly between India, and the UK, so I adapt quickly to your timezone. US, UK and European hours all work.
Stack / languages: Python (down to CPython internals), machine learning, LLMs, data structures and algorithms, system design.
Experience level: ML research at MIT, software engineering experience, and two years mentoring engineers with 10 to 15+ YOE.
Goal: To mentor experienced engineers (10+ YOE) who want to deeply understand Python, ML or LLMs, or make a career switch such as SWE to ML.
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Mentoring is 1:1, and I take a small number of people, usually senior engineers with 10+ YOE. Comment or DM me with your background and what you want to go deeper on.
Think you know the answers? Drop them in the comments. I'll tell you whether your mental model holds.