Each employer's screening rewards different signals. These guides cover what to emphasize per company — then tailor to the specific job description, which is what their ATS actually ranks you against.
Google's screening emphasizes impact at scale, quantified rigor, and the 'X-Y-Z' bullet formula its own recruiters popularized — resumes that survive show measurable outcomes with methods, not responsibility lists.
Amazon screens resumes against its Leadership Principles — Ownership, Customer Obsession, Deliver Results — so bullets that read as principle evidence with hard numbers dramatically outperform generic achievement lists.
Microsoft screening rewards growth-mindset framing, collaboration evidence, and stack alignment (Azure, .NET where relevant) — with clear weight on learning trajectories and cross-team impact in its post-2015 culture.
Meta's screening leans on impact-per-time — velocity of shipping, metric ownership, and scale — with resumes expected to show what moved because of you, fast, and interviews probing execution speed behind the bullets.
Apple screens for craft depth and quality obsession within a specific discipline — resumes narrower and deeper beat broad generalists, and secrecy culture means they respect impact described without confidential specifics.
Netflix hires senior, autonomous 'fully formed adults' per its culture memo — resumes need judgment and ownership evidence at significant scope, since the company famously pays top-of-market for people who need no runway.
TCS screening is volume-driven and keyword-literal: role-matched skills, certifications, and clean formatting decide the ATS pass, with domain experience (BFSI, healthcare, retail) heavily weighted for lateral positions.
Infosys lateral screening filters on skill-role matrices and certification checkboxes, with digital-stack keywords (cloud, data, automation) prioritized as the company repositions delivery toward higher-value services.
Wipro's lateral hiring screens for immediate billability: exact stack matches to open client requisitions, notice-period feasibility, and hands-on project evidence outrank breadth or potential in the initial pass.
Accenture screens for consulting-plus-technology hybrids: stack keywords get you matched, but client-facing evidence — workshops, stakeholder management, transformation outcomes — determines level placement and interview trajectory.
Deloitte screening weights structured achievement framing, industry alignment, and advisory polish — resumes are read as client deliverables, so formatting discipline and quantified engagement outcomes carry unusual weight.
Flipkart screens for scale-under-constraint evidence — systems and operations built for Indian e-commerce volumes (sale events, logistics complexity) — and weights problem-solving depth from strong engineering or tier-1 backgrounds.
Zomato (Eternal) screening favors speed, ownership, and consumer-product instincts — resumes showing shipped features with adoption numbers and scrappy problem-solving beat pedigree-heavy but outcome-light profiles.
Swiggy screens for real-time and marketplace problem exposure — logistics, dispatch, three-sided marketplace dynamics — plus data-driven iteration evidence, valuing candidates who've handled operational complexity at consumer scale.
Paytm screens for fintech-grade reliability signals — payments, transactions, compliance context — alongside scale numbers, weighting candidates who've built money-movement systems where failure has direct financial consequence.
Razorpay screens for API-product craftsmanship and payments-infrastructure depth — clean engineering signals (design docs, testing discipline, uptime numbers) matter because their product is developer-facing reliability itself.
Uber screens for distributed-systems and marketplace-scale evidence — real-time matching, geospatial complexity, and metric-owned execution — with resumes expected to carry hard scale numbers and end-to-end ownership stories.
Goldman screening pairs technical or analytical rigor with finance-context signals — precision, risk awareness, and quantified deliverables — and its formal process weights academics and structured achievement more than tech-startup screens do.
JPMorgan screens for engineering-at-bank-scale evidence — regulated-environment delivery, legacy-modernization wins, and stability metrics — valuing candidates who ship within controls without treating compliance as friction.
Adobe screens for product-craft and creative-domain affinity alongside solid engineering — performance work, rendering or document-technology depth where relevant, and evidence of building polished user-facing software.
NVIDIA screens for depth in accelerated computing — CUDA, systems performance, and ML infrastructure evidence beat generic software bullets, and resumes that quantify throughput, latency, or model-training impact match how their teams hire.
Oracle's volume hiring in India and enterprise accounts screens keyword-literally for Java, databases, cloud (OCI where named), and client-delivery tenure — clean ATS formatting and exact stack matches decide the first pass.
Tesla screens for high-ownership engineering under ambiguity — resumes that show first-principles problem solving, manufacturing or embedded adjacency where relevant, and aggressive delivery cadence outperform polished but incremental career stories.
Salesforce screens blend product-cloud craft with customer-zero thinking — Apex/Lightning or core platform keywords matter for IC roles, while Trailhead certifications and enterprise CRM delivery stories weigh heavily for India consulting tracks.