InterviewCompany
Professional graph, recommendations, search, data pipelines, and backend design practice.
Generate graph-based candidates, rank them, filter unsafe results, and evaluate acceptance.
Use mutual connections, profile similarity, company/school signals, privacy rules, ranking models, and feedback loops.
Use users and edges with relationship metadata and efficient traversal indexes.
Discuss directed versus undirected relationships, edge types, privacy, fanout, and graph partitioning.
Retrieve matching jobs, rank by relevance and quality, personalize, and diversify.
Features may include title match, skills, location, seniority, company preference, freshness, and application likelihood.
Measure sends, opens, dismissals, unsubscribes, and downstream engagement.
Segment by notification type, frequency, user cohort, and time. Look for diminishing returns and negative actions.