In [24]: # faang_by_company.ipynb
Abstract
The FAANG group (Google, Meta, Amazon, Apple, Netflix) is the most well-documented ML engineer compensation tier in the industry, with extensive Levels.fyi self-report data and mature banded levelling systems. Senior L5 base salary across the five companies averages $200,000 to $280,000 with total compensation $310,000 to $520,000 in 2026. Netflix is an outlier with all-cash base salary of $400,000 to $550,000+ for senior IC engineers and no separate RSU grant [1].
1 Bands from Levels.fyi Google, Meta, Amazon, Apple, Netflix, May 2026.
table fg-1 : FAANG side-by-side
| Company | L5 base | L5 total comp | Note |
|---|---|---|---|
| Google (Alphabet) | $210k - $260k | $320k - $470k | DeepMind integration adds research-track upside; long-standing ML org |
| Meta (Facebook) | $220k - $280k | $340k - $520k | Reality Labs and GenAI investment; high-RSU comp culture |
| Amazon (incl. AWS AI) | $160k - $220k | $280k - $420k | Base cap of ~$220k for many years; equity vests irregularly (5/15/40/40) |
| Apple | $200k - $260k | $300k - $470k | Strong AI/ML org since 2023 ramp; lower base than Meta but improving |
| Netflix | $400k - $550k+ | $400k - $550k+ all cash | Flat-org top-of-market base; no separate RSU grant for most ICs |
section fg-2 : individual mechanics
Google (Alphabet)
Google's ML organisation is the largest and longest-established in the FAANG group, with structural integration with DeepMind (acquired 2014) that gives senior ML engineers access to research-track promotions and rotations. L5 ML engineer base salary $210,000 to $260,000 with total compensation $320,000 to $470,000. RSU vesting on a back-loaded 4-year schedule (typically 33/33/22/12). Annual cash bonus 15 to 25 percent of base, plus refresh RSU grants starting year 2. Google's promotion calibration is the most thorough in FAANG, with defined criteria for L5, L6, and L7 ML engineers. The DeepMind integration is particularly valuable for research-oriented ML engineers; the standard product-engineering ML path runs parallel and is also well-supported.
Meta (Facebook)
Meta has invested heavily in Reality Labs (VR/AR ML) and GenAI since 2022, with corresponding compensation inflation for senior ML engineers. L5 base $220,000 to $280,000 with total compensation $340,000 to $520,000. Meta uses a more RSU-heavy compensation structure than Google or Amazon, with initial RSU grants often 50 to 60 percent of total 4-year compensation. Refresh grants starting year 2 typically $100,000 to $250,000 for ML engineers in retention scenarios. Meta's ML org spans recommendations (Feed, Reels, Ads), Reality Labs (VR/AR computer vision and speech), GenAI (LLaMA family and downstream applications), and ML infrastructure. Compensation is similar across these sub-orgs at L5; sub-org choice affects promotion velocity and scope.
Amazon (incl. AWS AI)
Amazon historically capped base salary at approximately $220,000 for most ML engineers, with the rest of total compensation delivered through signing bonuses (paid years 1-2) and back-loaded RSU vesting (5/15/40/40 four-year schedule). The cap was relaxed in 2022-2023 for many teams. L5 base $160,000 to $220,000, with newer band variations to $250,000+ for ML roles. Total compensation $280,000 to $420,000. Amazon's Applied Scientist track (L6+ in the SDE ladder but with additional research focus) is a distinct compensation path with above-band offers for senior research-focused ML engineers. AWS AI (Bedrock, SageMaker, Trainium) has been growing rapidly since 2023 with corresponding compensation competitive pressure.
Apple
Apple ramped its AI/ML organisation substantially in 2023-2024 with the introduction of Apple Intelligence (the on-device LLM product family) and corresponding hiring acceleration. L5 ML engineer base $200,000 to $260,000 with total compensation $300,000 to $470,000. Apple's compensation has historically run below FAANG peers but improved in 2023-2024 to match competitive offers. Apple ML work is concentrated in Cupertino and Seattle with smaller offices in other US metros. The on-device ML focus (running models efficiently on Apple silicon) is a distinct technical specialisation from cloud-ML at peer companies; senior Apple ML engineers tend to specialise in on-device deployment, model compression, and quantisation.
Netflix
Netflix operates a flat-org structure with senior IC ML engineer titles encompassing what other FAANG would split into L5 and L6 levels. Compensation is delivered as all-cash base salary of $400,000 to $550,000+ for senior IC engineers, with no separate RSU grant. The all-cash structure is distinctive in the industry: Netflix employees can take up to 100 percent of their compensation as cash, or allocate a portion to RSU equivalents at their discretion. Most senior Netflix ML engineers take the majority of their compensation as cash. Netflix ML work concentrates on content recommendation, content personalisation, and streaming-quality ML; the AI/GenAI investment is smaller and more applied than at other FAANG.
section fg-3 : the 2026 tradeoff
The senior ML engineer compensation comparison most often made in 2026 is FAANG versus frontier AI lab. FAANG offers stable, public-stock-RSU compensation in the $310,000 to $520,000 range at L5. Top frontier labs (OpenAI, Anthropic) offer pre-IPO equity packages in the $650,000 to $1,100,000 range at equivalent senior IC level. The headline numbers favour frontier labs by approximately 2x.
The risk-adjusted comparison is closer. FAANG RSUs are public-stock and convert to realised cash on vesting; frontier-lab equity is illiquid and contingent on the lab's continued success. A probability-weighted expected value of frontier-lab equity that discounts for company-failure scenarios still favours the frontier lab in most scenarios, but the variance is dramatically higher. For ML engineers with strong risk tolerance and earlier career stage, the frontier-lab offer typically wins. For mid-career engineers with significant unvested FAANG RSUs and family obligations, the FAANG offer wins more often.
A second axis: research scope. Frontier-lab work is closer to foundation-model research; FAANG ML work is closer to product engineering with large-scale ML systems. ML engineers prioritising intellectual scope of foundation-model work should weight this alongside the financial math.
section fg-4 : common questions
What is the average FAANG ML engineer salary in 2026?
FAANG ML engineer L5 senior compensation averages base $200,000 to $280,000 with total compensation $310,000 to $520,000 across the five FAANG companies, with substantial variation between companies. Netflix is an outlier with top-of-market all-cash base salary of $400,000 to $550,000+ for senior IC engineers and no separate RSU grant. The other four FAANG companies (Google, Meta, Amazon, Apple) use base-plus-RSU structures with varying base-vs-equity weights.
Which FAANG company pays the most for ML engineers?
Netflix on cash base salary; Meta on RSU-heavy total compensation; Google on stability and progression depth. Netflix's flat-org structure pays base salaries that exceed many FAANG peers' total compensation, but with no equity grant: a Netflix L5-equivalent ML engineer earning $475,000 base receives $475,000 total. Meta's L5 total compensation can exceed $450,000 in good stock-price years with refresh grants. Google sits between, with strong career-progression certainty.
What does L5 ML engineer compensation look like at Google?
Google L5 (Senior Software Engineer) ML role compensation in 2026: base $210,000 to $260,000, initial 4-year RSU grant approximately $400,000 (back-loaded vest: 33/33/22/12 typically), annual bonus 15 to 25 percent of base, annual refresh grant starting year 2 approximately $80,000 to $180,000. First-year total compensation approximately $350,000 to $440,000. Steady-state (year 2-4) total compensation approximately $320,000 to $470,000. DeepMind integration gives Google L5 ML engineers access to research-track promotions and rotations not available at other FAANG.
How does Amazon's L6 ML engineer compensation work given the $220k base cap?
Amazon historically capped base salary at approximately $220,000 for senior engineers including ML engineers, with the rest of total compensation delivered through sign-on bonuses (paid over years 1-2) and back-loaded RSU vesting (5/15/40/40 four-year schedule). An L6 (Principal Engineer) Amazon ML engineer in 2026 typically earns base $185,000 to $220,000, plus year-1 signing bonus of $100,000 to $200,000, plus year-2 signing bonus of $80,000 to $150,000, plus 4-year RSU grant of approximately $800,000 to $1,500,000 (back-loaded). First-year total comp $360,000 to $540,000; year-3-4 total comp $400,000 to $700,000 as RSU vesting ramps. Amazon raised some base bands above $220k in 2022-2023; bands now vary more by team.
What is the FAANG career trajectory for ML engineers?
Typical FAANG ML engineer trajectory: L3 entry, L4 promo at 1-2 years, L5 promo at 2-4 years from L4, L6 promo at 3-5 years from L5. Total approximately 6-11 years from entry to L6 staff. FAANG promotion timing is generally faster than enterprise tech employers (more competitive pressure forces calibration) and slower than fast-growth AI startups (which can promote by title at any time). FAANG career-stage compensation: L3 approximately $200k TC, L4 approximately $260k, L5 approximately $370k, L6 approximately $530k, L7 approximately $760k as 2026 averages.
Do FAANG companies pay more for LLM and GenAI specialisation?
Yes, all five FAANG companies have implemented some form of LLM and GenAI specialisation premium since 2023. The premium structure varies: Meta and Google have used aggressive sign-on bonuses and accelerated refresh grants for senior LLM engineers; Amazon has created Applied Scientist L6+ roles with above-band compensation; Apple has reportedly used non-public off-band offers for senior LLM engineers; Netflix's flat-org base structure means LLM specialists are paid at the top of the IC band. Across FAANG, the LLM and GenAI specialisation premium ranges 15 to 35 percent above generalist L5 ML engineer total compensation.
Is FAANG ML engineering still a good career choice in 2026?
Yes for most ML engineers, with the caveat that frontier AI labs now offer materially higher total compensation for ML engineers with foundation-model expertise. FAANG strengths are: stable employment, predictable promotion, mature engineering infrastructure, strong benefits, and access to large-scale ML systems. FAANG weaknesses relative to frontier labs are: lower top-of-distribution comp, less foundation-model research scope, more product-engineering focus versus pure research. For ML engineers seeking maximum total compensation, frontier-lab offers should be evaluated. For ML engineers prioritising career stability and broad-scope product impact, FAANG remains a strong choice.