Company Specific Questions¶
Company List¶
Tier 1 Companies (Comparable to Google):¶
Note
Meta: Strong focus on DSA, system design, and applied ML. Known for technical depth.
Amazon: Focus on DSA, behavioral interviews (STAR method), and practical ML applications.
Apple: Strong on applied ML and DSA; system design is often tailored to your domain.
Netflix: Interviews focus on practical ML problem-solving, coding, and cultural fit.
LinkedIn: Emphasis on data-centric ML systems, DSA, and ML system design.
DeepMind (non-research roles): Excellent for applied ML and generative models.
Tier 2 Companies (High-growth, strong ML teams):¶
Note
Uber: Focuses on optimization problems, practical ML, and system design.
Airbnb: Heavy on applied ML, personalization systems, and coding.
Stripe: Emphasis on practical problem-solving and ML engineering.
Snowflake: Strong in data platforms and ML infrastructure.
Databricks: Focused on ML engineering, distributed systems, and applied ML.
Tier 3 Companies (Well-funded startups or specialized domains):¶
Note
OpenAI: Opportunities in applied ML and generative AI (non-research roles).
NVIDIA: Strong in generative AI and ML systems.
Scale AI: Applied ML roles focused on annotation and ML pipelines.
Spotify: Personalization and recommendation systems.
Adobe: Deep expertise in generative and applied ML.
- Adobe
- Amazon
- Atlassian
- Preparation Guide
- Sample ML Problems
- Design a Content Recommendation System for enhancing knowledge discovery in Confluence Cloud
- Intelligent Q&A System for improving knowledge sharing in Confluence Cloud
- Enhance the search and recommendation features in Jira Cloud
- Design an Intelligent Chatbot for improving customer support in Jira Service Management
- Design a Recommendation Engine for improving task management in Trello
- Products and ML Problems
- Sample Questions
- Meesho
- Meta
- Mistral
- NetApp