The Complete AI Engineer Roadmap
Phase 4 of 5

ML System Design + Interview Prep

Master interview-grade skills — DSA, ML System Design, ML Breadth, polished portfolio.

Weeks 25-32 · Months 7-8~112 hours · 8 weeks

All 5 Phases

Week-by-Week Schedule

Week 25 — DSA Sprint Part 1: Arrays, Strings, Hash Maps

Two pointers pattern · Sliding window · Hash maps / sets · Prefix sum · …

7 daily tasks

Week 26 — DSA Sprint Part 2: Trees, Graphs, DP

Binary trees: DFS (pre/in/post), BFS · BST operations + LCA · Graphs: BFS/DFS, connected components · Topological sort, Union-Find · …

7 daily tasks

Week 27 — ML System Design Framework

The 8-step framework · Steps 1-2: Requirements, metrics · Steps 3-4: ML problem framing, data strategy · Steps 5-6: Feature engineering, model architecture · …

7 daily tasks

Week 28 — ML System Design Practice (5 Case Studies)

Tue — Search & Ranking System — Aminian · Thu — Ad Click Prediction at Scale — Aminian · RAG Chatbot Architecture — use your Project 3 as starting point · Content Moderation System — Aminian · …

5 daily tasks

Week 29 — DSA Sprint Part 3: Hard Patterns

Backtracking: subsets, permutations, N-queens · Greedy: interval scheduling, jump game · Binary search variants · Trie problems · …

7 daily tasks

Week 30 — ML Breadth Interview Review

Why gradient descent works. Cross-entropy derivation. · Bias-variance tradeoff. L1 vs L2. · Batch norm vs Layer norm. Vanishing gradients + ResNet. · Adam math (first + second moments). MSE vs cross-entropy. · …

7 daily tasks

Week 31 — Resume + GitHub Polish + Behavioral Stories

Rewrite resume (Action verb → What → Result with numbers) · Polish all GitHub repos: clean READMEs, architecture diagrams, demo GIFs · Build portfolio website (GitHub Pages + template) · LinkedIn profile overhaul — keywords for recruiter search · …

7 daily tasks

Week 32 — Full Mock Interview Loops

Pramp DSA mock · Pramp behavioral mock · interviewing.io DSA mock or another Pramp · ML system design mock with peer · …

7 daily tasks

Topics Covered

Every subtopic below is a separate daily task in the roadmap, with hand-picked resources (YouTube videos, docs, papers) for each.

  • Two pointers pattern
  • Sliding window
  • Hash maps / sets
  • Prefix sum
  • Mock interview practice on Pramp
  • Catch-up + pattern review
  • Blind 75 progress — aim for 15 problems done
  • Binary trees: DFS (pre/in/post), BFS
  • BST operations + LCA
  • Graphs: BFS/DFS, connected components
  • Topological sort, Union-Find
  • DP basics: climbing stairs, coin change
  • DP intermediate: LIS, edit distance
  • Heaps: top-K, merge K sorted lists
  • The 8-step framework
  • Steps 1-2: Requirements, metrics
  • Steps 3-4: ML problem framing, data strategy
  • Steps 5-6: Feature engineering, model architecture
  • Steps 7-8: Training pipeline, serving + monitoring
  • Case Study 1: Video Recommendation System (YouTube)
  • Write your own design doc for the case study
  • Tue — Search & Ranking System — Aminian
  • Thu — Ad Click Prediction at Scale — Aminian
  • RAG Chatbot Architecture — use your Project 3 as starting point
  • Content Moderation System — Aminian
  • Fraud Detection (imbalanced, real-time) — Aminian
  • Backtracking: subsets, permutations, N-queens
  • Greedy: interval scheduling, jump game
  • Binary search variants
  • Trie problems
  • Bit manipulation basics
  • Hard DP: knapsack, LCS
  • Mock interview on Pramp + review
  • Why gradient descent works. Cross-entropy derivation.
  • Bias-variance tradeoff. L1 vs L2.
  • Batch norm vs Layer norm. Vanishing gradients + ResNet.
  • Adam math (first + second moments). MSE vs cross-entropy.
  • Self-attention from scratch. Q/K/V.
  • LoRA math + why it works. RLHF end-to-end. KV cache.
  • SFT vs RLHF vs DPO. Build Anki deck of 100+ Q&A.
  • Rewrite resume (Action verb → What → Result with numbers)
  • Polish all GitHub repos: clean READMEs, architecture diagrams, demo GIFs
  • Build portfolio website (GitHub Pages + template)
  • LinkedIn profile overhaul — keywords for recruiter search
  • Prepare 8 STAR stories (Eldan's page 14)
  • Practice STAR stories out loud, record yourself
  • Get resume reviewed: r/EngineeringResumes or senior
  • Pramp DSA mock
  • Pramp behavioral mock
  • interviewing.io DSA mock or another Pramp
  • ML system design mock with peer
  • ML breadth mock with peer
  • Review all feedback, identify weak spots
  • Focused drilling on weak spots