New Grad Recruiting 2026
Machine Learning New Grad Guide
Track-specific prep for ML Engineer, Applied Scientist, Research Scientist, and Quant ML roles. Each track has a completely different interview โ select yours for the exact topics that matter.
โ๏ธ ML Engineer Track
Build, deploy, and scale ML systems. Heavy coding emphasis, strong SWE foundations required. Think: making models work in production at millions of QPS.
Top Skills Needed
Target Companies
ML Engineer Topics(9 topics โ unique to this track)
Click to expand full breakdownCompany-Specific Prep
Click a row to see insider notes4-Month Action Plan
Starting April 2026 โ recruiting season peaks JulyโSeptember 2026
April
Foundations
- โNeetCode 150: Trees + DP + Graphs (do 3/day)
- โComplete all ML fundamentals section
- โSet up a ML portfolio project on GitHub
- โRead ISLR Chapters 2-8
May
Deep Learning
- โBuild transformer from scratch (Karpathy's nanoGPT)
- โCS231n lectures 1-10
- โRead Attention, BERT, InstructGPT papers
- โFine-tune a model on a real dataset
June
Systems & Stats
- โRead 'Designing ML Systems' (Chip Huyen)
- โDesign 5 full ML system design problems
- โA/B testing + causal inference deep dive
- โBuild end-to-end ML project with deployment
July
Interview Grind
- โ2 mock interviews per week (Pramp/Interviewing.io)
- โFirm-specific research per company target
- โPolish project portfolio + resume narrative
- โTimed Blind 75 daily โ track your weak spots
ML recruiting is a marathon โ start now.
The students who land top ML roles start 4+ months early, build real projects, and treat interview prep like a second job. Each track is genuinely different โ pick yours and go deep. ๅ ๆฒน!!