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Each pack is curated for a specific company and role. You get the actual interview process, what they value, the topics tested, and a pre-filtered set of practice questions that match what shows up in the real loop. Engineering manager and ML engineer loops have their own packs below the software engineer ones.
New grad / entry-level prep for Google's SWE loop, calibrated to L3 expectations.
Curated practice for the Google SWE interview loop, calibrated to L4 expectations.
Senior-level prep for Google's L5 loop - higher coding bar, deeper system design, and senior Googleyness signal.
Staff-level prep for Google's L6 loop - two system design rounds, tech leadership signal, and a dramatically higher bar than L5.
Senior Staff prep for Google's L7 loop - architecture review depth, cross-org technical strategy, and very few external hires.
Entry-level prep for Amazon's SDE I loop - coding fundamentals plus Leadership Principles, scaled to a new-grad bar.
Curated practice for Amazon's SDE II loop, with a heavy focus on Leadership Principles.
Senior-level prep for Amazon's L6 loop - deeper system design, tougher Bar Raiser, and Leadership Principles probed at multi-team scope.
Principal-level prep for Amazon's L7 loop - architecture review, org-level Leadership Principles, and a bar dramatically above Senior SDE.
Practical, applied prep for Stripe's notably hands-on backend interview loop.
Mid-level prep for Meta's E4 loop - high coding bar, one system design round, and mid-level behavioral signal.
Curated practice for Meta's E5 loop - heavy on system design and senior-level behavioral signal.
Practical prep for Anthropic's applied engineering loop - take-home project, writing-heavy culture, and genuine engagement with AI safety.
Entry-level prep for Microsoft's SDE I loop - balanced coding fundamentals, light system design, and Growth Mindset framing.
Curated prep for Microsoft's SDE II loop - balanced coding, system design, and Growth Mindset behavioral rounds.
Senior IC prep for Microsoft's Senior SDE loop - two design rounds, senior behavioral signal, and tech leadership expected.
Principal-level prep for Microsoft's loop - architecture review, technical strategy, and Growth Mindset at organizational scope.
Prep for OpenAI's applied engineering loop - strong algorithms, ML infrastructure design, and genuine mission alignment.
Prep for SpaceX's hands-on engineering loop - strong CS fundamentals, C++ and Python depth, real-world problem solving, and genuine mission pull.
Prep for Databricks' engineering loop - distributed data systems, strong coding fundamentals, and deep technical depth on data infrastructure.
Prep for Snowflake's database-internals-heavy loop - C++/Java depth, query engines, distributed storage, and one of the highest systems bars in data infrastructure.
Prep for Coinbase's pragmatic, values-driven loop - practical pair-programming rounds, exchange-flavored system design, and a real emphasis on security thinking.
Prep for Apple's team-specific engineering loop - deep technical depth, strong fundamentals, and team-specific domain knowledge.
Prep for Netflix's notably high-context engineering loop - 'Senior' is the entry rung, the bar is steep, and the culture deck is real.
Prep for NVIDIA's engineering loop - heavy systems and parallel computing emphasis, deep CUDA/GPU domain knowledge for many roles.
Prep for Uber's senior IC loop - distributed systems depth, location-aware design, and cultural emphasis on ownership and impact.
Prep for Airbnb's product-engineering-heavy loop - strong coding fundamentals, frontend or backend depth, and the famous 'living the values' round.
Prep for LinkedIn's engineering loop - strong coding fundamentals, distributed systems depth, and Microsoft-influenced behavioral framing.
Prep for Tesla's mission-driven engineering loop - hardware-software interplay, autopilot ambition, and a culture that rewards velocity over process.
Prep for TikTok's engineering loop - high coding bar, recommendation-system depth, fast iteration culture, and the ByteStyle values screen.
Prep for Figma's craft-first engineering loop - browser-tech depth, design partnership, and the unusually applied take-home that defines the process.
Prep for Notion's product-engineering-heavy loop - applied coding, AI integration depth, productivity-tooling sensibility, and strong cross-functional product sense.
Prep for Salesforce's enterprise SaaS engineering loop - multi-tenant architecture depth, Apex/Lightning ecosystem fluency, and a structured ladder that runs deep.
Prep for Adobe's engineering loop - creative-tooling craft, performance depth, and the GenAI integration push that defines Adobe's 2026 product strategy.
Prep for Discord's engineering loop - real-time voice/video infrastructure, Elixir/Erlang depth, low-latency systems, and the unusual scaling challenges of large guilds.
Prep for Canva's engineering loop - design tooling at scale, canvas/WebGL depth, freemium product mechanics, and the Magic Studio AI integration push.
Prep for Ramp's engineering loop - fintech depth, finance integrations, growth-stage scaling, and a culture that rewards velocity and customer obsession.
Prep for Rippling's engineering loop - unified HRIS / IT / finance platform, multi-tenant SaaS depth, API-first architecture, and the unusually broad product surface.
Prep for Linear's engineering loop - product engineering at small-team scale, real-time sync depth, design partnership, and the performance-obsession that defines the brand.
Prep for Perplexity's engineering loop - AI-native search, retrieval and RAG depth, LLM serving at scale, and the velocity expected at one of the fastest-growing AI products.
Prep for Jane Street's interview loop - OCaml-first engineering, mental-math under pressure, probability and game-theory puzzles, and a culture built around training rather than hiring for direct experience.
Prep for Two Sigma's engineering loop - quantitative research infrastructure, Python and JVM depth, large-scale data systems, and the research-engineer collaboration model.
Prep for the Citadel and Citadel Securities loops - low-latency C++ depth, market microstructure literacy, hedge fund vs market-making team alignment, and a famously rigorous interview process.
Prep for HRT's interview loop - C++ and low-latency systems depth, algorithmic and statistical reasoning, and the small-team / research-leaning culture that distinguishes HRT from larger trading firms.
Prep for Atlassian's engineering loop - enterprise SaaS at multi-million-customer scale, Jira/Confluence/Bitbucket platform depth, the cloud migration story, and a values-driven culture with a notably structured behavioral process.
Prep for ServiceNow's engineering loop - the Now Platform at enterprise scale, workflow automation depth, AI integration, and the platform-engineering culture that powers Fortune 500 IT and business process automation.
Prep for IBM's engineering loop - hybrid cloud and AI focus (Red Hat, watsonx, IBM Cloud), enterprise customer scope, the broad business unit landscape, and a culture mid-transformation toward modern engineering practices.
Prep for Oracle's engineering loop - Oracle Cloud Infrastructure (OCI) growth story, database depth, the legacy applications business modernization, and the engineering culture mid-pivot from on-premise enterprise software to cloud.
Prep for Riot's engineering loop - live game services at the scale of League of Legends and Valorant, real-time multiplayer infrastructure, anti-cheat, and the player-experience-first engineering culture.
Prep for Roblox's engineering loop - the user-generated content platform at hundreds-of-millions-of-users scale, real-time game infrastructure, the creator economy, AI-driven moderation and creation tooling, and the unusual engineering challenges of running both an engine and a platform.
Prep for Google's EM loop: people leadership, org-level system design, and a technical bar that does not go away.
Prep for Meta's EM loop: people management depth, a past-project deep dive, and system design.
Prep for Amazon's SDM loop: Leadership Principles in every round, a Bar Raiser, and system design.
Prep for Microsoft's EM loop: people leadership, growth mindset, system design, and the final 'as appropriate' round.
Prep for Apple's team-run EM loop: deep technical expertise, people leadership, and craft.
Prep for Netflix's EM loop: the culture memo as a rubric, talent density, and context-not-control leadership.
Prep for Stripe's EM loop: people leadership, writing-heavy collaboration, and payments-grade system design.
Prep for Uber's EM loop: people leadership, execution in a real-time marketplace, and system design.
Prep for Airbnb's EM loop: people leadership, product partnership, system design, and the core values interview.
Prep for Databricks' EM loop: a high technical bar, distributed-systems design, and people leadership.
Prep for Google's ML engineering loop: the full SWE coding bar plus ML domain and ML system design rounds.
Prep for Meta's Software Engineer (ML) loop: fast coding, ML system design for ranking, and behavioral.
Prep for Amazon's ML engineering loop: Leadership Principles everywhere, coding, ML depth, and ML system design.
Prep for Microsoft's ML loops: coding, ML fundamentals, a deep dive on your work, and growth mindset.
Prep for Apple's team-run ML loop: ML depth in the team's domain, coding, and privacy-aware system design.
Prep for Netflix's ML loop: personalization, experimentation, ML system design, and the culture memo.
Prep for Uber's ML loop: marketplace ML problems, production ML systems, and coding.
Prep for Databricks' ML loop: a strong coding bar, ML platform and distributed training design, and ML fundamentals.
Prep for OpenAI's ML and research engineering loops: practical coding, ML depth, ML infrastructure design, and mission.
Prep for NVIDIA's ML loops: deep learning depth, GPU performance, distributed training and inference, and coding.
Generic interview prep is broad. Real interview loops are specific. Google asks about Googleyness. Amazon weights Leadership Principles across every round. Stripe wants you to write working code with tests. Meta runs two system design rounds at E5. The right preparation matches the company you're targeting.
Each pack pulls from gitGood's full question and challenge library, filtered to the topics that round-by-round match the actual loop at that company. You get the interview process, what each round signals, the topics emphasized, and behavioral framing tailored to the company. Free tier gives you a preview; premium unlocks all questions across every pack.
We're adding more packs regularly. Want to suggest a company, role, or level we're missing? Let us know.