With the rapid development of the AI field in recent years, Anthropic has been attracting attention as a leader in the industry, attracting the attention of countless AI talents. If you are interested in joining this leading AI research company, understanding its interview process and focus is a crucial step. Based on the Anthropic interview experience experienced by the PROGRAMHELP team, this article reveals the key elements that the company focuses on during the hiring process, which will hopefully help you prepare for Anthropic interview provides valuable reference.
Overall process: rigorous and focused on depth of competencies
Based on existing shares, Anthropic's interview process generally includes:
- Resume Screening and Initial Communication: Phone or video for basic information.
- Multiple rounds of technical interviews: looking at machine learning, deep learning, algorithms, data structures and business application ideas.
- System Design Interview: Evaluate distributed systems, scalability and reliability design capabilities.
- Behavioral Interview/Culture Fit: Understand communication, collaboration, and AI ethics through past experiences.
- Team Member Networking: In-depth discussions with prospective colleagues or fellows to assess collaborative fit.
Interviews can be lengthy, with multiple rounds running in parallel to ensure the best match is found.
Anthropic Interview Questions Sharing
Coding
Question: Design a simple post-processing system for text generation. Given a list of texts generated by a large language model generated_texts, complete:
- Remove repetitive sentences (starting with "." , "!" , "?" endings);
- Filters text less than 10 words long;
- Sort by text length from longest to shortest.
Example Input:
generated_texts = [
"This is a sample sentence. Another sample sentence.", "Short text.", "Another sample sentence.", "Another sample sentence.", "This is a sample sentence.
"Short text.", "This is a longer text with multiple sentences.
"This is a longer text with multiple sentences. And another one.", "This is a sample sentence.", "This is a sample sentence.", "This is a longer text with multiple sentences.
"This is a sample sentence."
And another one.", "This is a sample sentence."]Sample Output:
[___
"This is a longer text with multiple sentences. And another one.", "This is a sample sentence.
"This is a sample sentence. Another sample sentence."
Another sample sentence."]System Design
Question: Design a distributed AI training data labeling platform that needs to satisfy:
- Data Management: 10 million text storage and retrieval, item/label categorization;
- Markup process: task assignment, multi-person collaboration, real-time synchronization;
- Quality Control: Automatically detects contradictory annotations and triggers secondary review;
- Extensibility: support for future image/audio multimodal annotation.
Design Requirements:
- Draw a system architecture diagram illustrating the core modules;
- Select technology stack (database, message queues, distributed frameworks);
- Discuss load balancing, data consistency solutions.
BQ
- Technological Challenges and Innovations:
Tell me about a time when you faced a complex technical problem... - Ethics and Responsibility:
Describe balancing technical feasibility with ethical considerations... - Learning and Growing:
Share how you learned a new technology to solve a problem... - Cross-team collaboration:
Tell me about working with a cross-functional team...
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