The Complete Interview Guide for AI & Biotech Roles
Interviewing for AI and biotech positions is a unique experience that blends technical assessment with scientific evaluation.
## AI/ML Engineering Roles (4-5 rounds)
**Round 1: Technical Screen (45-60 min)**
- Implementing ML algorithms from scratch
- Python/numpy coding problems
- Basic statistics and probability
**Round 2: ML System Design (60 min)**
- Design a recommendation system for scientific papers
- Build a pipeline for classifying medical images
**Round 3: Deep Dive / Research Discussion (60 min)**
- Present and defend your past work
- Methodology and design decisions
**Round 4: Behavioral / Culture Fit (45 min)**
- Domain-specific scenarios
## Biotech / Computational Biology Roles (5-6 rounds)
**Round 1: Technical Screen** — statistics, genomics, bioinformatics tools
**Round 2: Scientific Presentation** — present your research to a panel
**Round 3: Journal Club** — read and critique a recent paper
**Round 4: Coding/Analysis Exercise** — real biological data analysis
**Round 5: Cross-Functional Interview** — communication and teamwork
## Preparation Strategies
### For Coding Interviews
- Practice on LeetCode, focusing on medium-difficulty problems
- Review ML algorithm implementations
- Know pandas, numpy, and scikit-learn APIs
### For System Design
- Study ML system design resources
- Practice designing systems end-to-end
- Understand trade-offs: batch vs. real-time, accuracy vs. latency
### For Scientific Presentations
- Prepare a 20-minute presentation on your best work
- Practice explaining at multiple levels of depth
## Common Mistakes to Avoid
1. **Over-engineering solutions** — start simple
2. **Ignoring the biological context** — understanding why matters
3. **Not asking questions** — show intellectual curiosity
4. **Neglecting soft skills** — technical excellence alone won't get you hired
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