Recently, one of my trainees successfully secured a top AI company Anthropic This is not only a result of his personal efforts, but also a success story of our joint planning, overcoming challenges and systematic preparation. Today, I'm organizing and sharing Anthropic's interview experience summarized from this journey, hoping to inspire those of you who are looking for jobs, especially targeting top tech companies.
Anthropic Interview Process
1. Initial screening: resumes should shine, and the conversation should flow smoothly
HR will look at resumes first, focusing on AI, data science, or engineering-related experience; followed by a phone call to understand background and motivation. Resumes should highlight hardcore projects and phone calls should be organized.
2. Online programming challenge: code fast and accurately
Usually on HackerRank or LeetCode, solve 2-4 moderately hard programming problems in 60-90 minutes. Focus on practicing arrays, graphs, and dynamic programming to improve time-limited coding skills.
3. Technical interviews: be technically solid and think clearly
Multiple rounds include coding, system design, machine learning fundamentals, and project discussions. The coding was written while the ideas were presented, and the project experience was organized using the STAR method.
4. Behavioral and cultural fit: strong sense of teamwork and alignment of values
Anthropic values collaboration and AI ethics and will ask about conflict resolution and leadership cases. Prepare true stories that demonstrate teamwork and understanding of AI security.
5. Values interview: AI security concepts to be in-depth
Delve deeper into perspectives on AI security and ethics. Understand the company's mission, provide insights in the context of your work, and demonstrate a values fit.
6. Virtual Onsite: an intensive test of composure
Entered virtual Onsite after pre-screening, includes more technical and behavioral interviews, may have Take-Home assignments. Time management and logical expression are critical.
Anthropic Interview Exclusive Questions
1. Optimization of intelligent dialogue system message distribution
Title:Given a list of messages messages(Each article contains user_id and content) to evenly distribute messages from the same user to the server_count servers to avoid overloading.
def assign_messages(messages, server_count).
# returns a list of assignments, assignments[i] is the server number assigned to message i
pass
2. Calibration of AI model inference results
Title:Given a list of predictions predictions(Each strip contains category together with confidence), threshold threshold hereinafter denoted as 'unknown'.
for pred in predictions: if pred['confidence'] < threshold.
if pred['confidence'] < threshold.
pred['category'] = 'unknown'
3. AI data annotation tasking
Title:there are tasks([difficulty, time](math.) and annotators([max_difficulty, max_time]), assigning tasks to maximize the number of completions.
def assign_tasks(tasks, annotators).
# Returns assignments, a list of task indices for each annotators[i].
assign_tasks(tasks, annotators): #
Still confused about preparing for an interview?
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