Netflix's SWE interview includes: 1) Technical phone screen (45-60 min coding), 2) Virtual on-site with 4-5 rounds covering algorithms, system design, and cultural fit, 3) Focus on Netflix's streaming and personalization challenges. Technical questions emphasize scalability, performance, and distributed systems. Cultural questions test alignment with freedom/responsibility, candid feedback, and high performance standards. Prepare for questions about video streaming, recommendation systems, and massive scale challenges.

While deep video streaming expertise isn't required, understanding the fundamentals helps: video encoding/decoding, adaptive bitrate streaming, CDN concepts, and network optimization. More important is demonstrating ability to think about scale, performance, and user experience. Study Netflix's tech blog, understand their microservices architecture, and be prepared to discuss how you'd solve large-scale distributed systems problems.

Netflix system design questions focus on streaming and scale: 'Design Netflix's video streaming architecture', 'Build the recommendation system', 'Design content delivery system', 'Handle traffic spikes during show releases', 'Build A/B testing platform'. Key concepts: microservices, CDN, caching, load balancing, real-time data processing, and global distribution. Always consider performance, reliability, and user experience at Netflix's scale.

Show examples of: making important decisions independently, taking ownership of outcomes (both successes and failures), giving and receiving candid feedback, prioritizing company success over personal comfort, and operating with minimal oversight. Netflix values high performers who can be trusted with significant responsibility and who contribute to maintaining high team performance standards.

Netflix SWE compensation is top-of-market: L4 (mid): $170k-230k base, $350k-550k total; L5 (senior): $200k-280k base, $450k-700k total; L6+ (staff): $250k+ base, $600k+ total. Netflix uses high cash compensation rather than equity, with annual market adjustments. Culture of high performance with excellent compensation, but also high expectations. Growth opportunities in streaming tech, ML/personalization, platform engineering, and international expansion.

Mid-level should frame high-level components, data flows, and scaling levers. Senior/staff are expected to discuss region failover, traffic shaping, resilience patterns (circuit breakers, bulkheads), cost vs latency trade-offs, observability signals (RED/USE), and how you'd evolve architecture under 10x load or new codec requirements.

Bring stories showing: autonomous decision with quantified impact, candid feedback you gave that changed a direction, owning a mistake transparently, deleting or simplifying a system to reduce drag, and proactively raising context to leadership. Emphasize judgment + impact over process compliance.

Adaptive bitrate ladder strategy, segment encoding, CDN edge cache hierarchy, manifest generation, prefetching, resilience to degraded network, and metrics (startup latency, rebuffer ratio, bitrates watched). You don't need precise FFmpeg flags—focus on performance & reliability trade-offs.

Typical topics: designing a scalable streaming or personalization service, implementing cache or rate limiter components, coding problems on data structures/algorithms (graphs, concurrency-safe structures), troubleshooting performance under traffic spikes, and culture fit scenarios about ownership & candid feedback. Expect 1–2 system design, 2 coding, 1 culture round.