Built for big tech recruiting

Big tech recruiting is its own ecosystem. The resume conventions, keyword expectations, and review processes at Amazon, Google, Meta, and Microsoft do not match what generic resume writers produce. A tech resume that lands at a regional SaaS company can underperform spectacularly at FAANG — and vice versa.

Profile Elevate works with CS, EE, ECE, data science, statistics, and applied math students targeting software engineering, product management, machine learning, data science, and infrastructure roles. We have helped candidates land roles at every FAANG company plus high-growth firms like Stripe, Databricks, Airbnb, Snowflake, and Anthropic.

The big tech funnel is unforgiving. ATS keyword screens reject 60 to 70 percent of applicants on the first pass. The next layer is a 30-to-90-second recruiter scan. Surviving both requires a resume engineered for the funnel — not a generic 'one-size-fits-all' document.

  • Per-company conventions: Amazon LPs, Google impact, Meta scope, Apple craft

  • Project bullets that read like production engineering

  • GitHub readiness review before you link from the resume

  • PM resume framework distinct from SWE

  • Data science / ML resume framework with model metrics

FAANG resume conventions, decoded

Every top tech company has unwritten resume conventions. A resume that crushes at Amazon underperforms at Google, and vice versa. We tune your resume per target company, not per generic ‘tech role’.

Amazon

STAR + Leadership Principles
  • Bullets must implicitly map to one of the 16 Leadership Principles (Customer Obsession, Ownership, Bias for Action, Dive Deep, etc.).
  • Quantify scale (requests/sec, users, dollars saved). Amazon loves big numbers.
  • Show ownership: lead language, not 'helped' or 'assisted'.

Google

Quantified impact + technical depth
  • Every bullet should answer: what did you do, how did you do it, what was the measurable result?
  • Mention specific languages, frameworks, and systems by name. Vague tech stacks fail screens.
  • Include systems-level impact: latency improvements, scalability, complexity reduction.

Meta

Speed, ownership, scope
  • Bullets emphasize impact velocity — how fast you shipped, how much scope you owned.
  • Cross-functional collaboration counts. Show alignment with PM and design partners.
  • Production system numbers (users impacted, MAU, performance gains) matter more than implementation detail.

Apple

Craft and product detail
  • Apple values polish and end-user impact over raw scale numbers.
  • Show product sensibility: features shipped, UX improvements, hardware/software integration.
  • Tighter writing wins — every word should justify being there.

Netflix

Senior-level scope expected
  • Netflix rarely hires new grads — when it does, expect senior-level resume scrutiny.
  • Bullets should demonstrate autonomy and judgment, not just execution.
  • Cultural alignment with the Netflix Culture Memo is a real screen.

Microsoft

Balanced scope + collaboration
  • Microsoft values both individual contribution and team-level outcomes.
  • Cloud (Azure), AI/ML, and enterprise productivity are the hot areas — tune keywords accordingly.
  • Strong fit for cross-functional engineers (security, infra, devtools).

What we cover for tech students

Choose the bundle that matches your goals — most candidates targeting FAANG start at Premium.

Resume writing

One-page, ATS-tuned resume with quantified project bullets, per-company keyword variants (FAANG, fintech, AI labs), and a tech-specific skills taxonomy.

  • Project bullets that read like production engineering
  • Per-company keyword variants
  • GitHub readiness review
Learn more →

LinkedIn optimization

Tech-recruiter-search-tuned LinkedIn. Featured section curation, project links, and About-section narrative that signals technical depth without overclaiming.

  • Recruiter Search keyword strategy for SWE / PM / DS
  • Featured section with project and GitHub links
  • Headline calibration for active vs. passive search
Learn more →

Career coaching

1:1 coaching covering behavioral interview prep (Amazon LP framework), target company list, referral request scripts, and FAANG application timeline.

  • Amazon Leadership Principles behavioral prep
  • Referral request scripts that work at FAANG
  • Application timeline back-timed from graduation
Learn more →

How it works

Four steps designed around the FAANG application timeline.

1

Discovery call

20-minute conversation about your target roles (SWE / PM / DS / infra), target companies, graduation date, and any active applications or referrals.

2

Intake & deep dive

Send us your current resume, GitHub URL, three to five target job descriptions, and your top-10 target company list. We map your projects to each company's conventions.

3

Draft & revise

Within 5 business days, you receive a tech-tuned resume, per-company keyword variants, a LinkedIn rewrite, and a GitHub polish checklist.

4

Launch

Final delivery plus a tailoring walkthrough on a real FAANG job description — you learn how to adjust the master resume per company in under 15 minutes.

Plans that fit tech students

Transparent USD pricing. No subscriptions, no surprise fees. Pick the level of support you need now and upgrade later if you want more.

Basic
$99

Resume review + LinkedIn polish to start strong.

  • Resume review & formatting
  • LinkedIn profile optimization
  • 1 round of revisions
View full pricing
Most popular
Intermediate
$149

ATS-tuned resume + LinkedIn for active job-search.

  • ATS-friendly resume rewrite
  • Keyword strategy for target roles
  • LinkedIn networking guidance
View full pricing
Premium
$249

Resume, LinkedIn and full career-marketing support.

  • Everything in Intermediate
  • Cover letter template
  • 1:1 career-marketing coaching
View full pricing

Tech student FAQ

The questions we hear most from CS, ECE, DS, and PM-track candidates.

Treat class projects like production systems. Instead of 'Built a web app for class project', write 'Designed and shipped a Flask/React expense-tracking app with PostgreSQL backend, supporting 200+ user accounts and 50 concurrent sessions in load testing.' Quantify users, scale, latency, throughput, or test coverage. Even projects without real users have measurable technical characteristics: lines of code reduced, latency improvements vs. naive implementation, accuracy metrics on ML projects. We rewrite every project bullet to read like a production engineering achievement.

Get a FAANG-tuned resume in under two weeks

Stop guessing about Amazon Leadership Principles, Google quantified impact, and Meta scope conventions. Work with coaches who tune resumes per target company.