First AI role, conceptual depth and fundamentals matter most.
Start with the basics: how text becomes tokens, how tokens become vectors, and how attention mixes those vectors.
By the end of this week, you can sketch how text becomes a token, how a token becomes a vector, and how attention mixes vectors.
First-round screens hammer these basics. Confident first-principles answers here unlock the rest of the loop.
Watch out: Memorizing the attention formula without the intuition is the trap. Practice explaining it in your own words first.
Learn the building blocks of modern AI apps: RAG, vector databases, and tokenization in context.
By the end of this week, you can sketch a small RAG app on a whiteboard from scratch.
Most fresher-role projects are some flavor of RAG. Knowing the moving parts beats deep theory you can't apply.
Watch out: Conflating tokenization with embeddings trips up most new grads. Practice the distinction out loud until it's automatic.
Survey the landscape: agents, fine-tuning, evaluation. Start drilling questions across all formats.
By the end of this week, you've drilled at least 30 mixed-format questions and know which 3 topics need the most revisit.
Breadth matters at junior levels. Showing curiosity across agents, fine-tuning, and evaluation signals you'll grow into the role.
Watch out: Sticking only to topics you already know is the comfort trap. Time-box your weak areas instead.
Focus on system design basics, inference optimization, and mixed-format practice under time pressure.
By the end of this week, you can sit a 45-minute mixed interview without notes and pace yourself.
Timed mixed-format practice is what catches you out on the day. Building the muscle now beats reading any single book again.
Watch out: Going long on the easy questions costs you the hard ones. Practice with a timer until pacing is automatic.