Scale AI Compensation in 2026: $234K–$642K+ by Level

Scale AI is the company that labels the data behind the biggest AI models in the world. Founded in 2016 by Alexandr Wang when he was 19, Scale has grown into a $29 billion AI infrastructure company with ~1,200 employees, $2B+ in projected annual revenue, and contracts with OpenAI, Meta, Microsoft, and the United States Department of Defense. If you’re considering a role at Scale, the first question is usually about compensation — and the numbers are strong.

We compiled verified compensation data from employee-reported salary databases, job postings, and our own research across 118 AI and tech companies to give you the clearest picture of what Scale AI pays in 2026 — by level, by role, and in context against comparable companies.

Scale AI at a Glance

Software Engineer Compensation by Level

Here’s what Scale AI pays software engineers at each level, based on verified employee-reported compensation data. All figures are total compensation (base + equity + bonus) for US-based roles.

The jump from L4 to L5 is the steepest — a ~45% increase, largely driven by a significant equity ramp at the senior level. At L5 and above, equity typically represents 40–50% of total compensation, which means the value of your package is closely tied to Scale’s trajectory as a company.

For Staff+ roles, Scale’s publicly posted salary ranges confirm competitive base pay. A Staff Software Engineer role in hub locations (SF, NYC, Seattle) lists a base range of $248,400–$310,500. With equity and bonuses, total comp pushes well past $600K.

How Scale Compares to Other AI Companies

Scale AI occupies an interesting position in the compensation landscape. It’s not a frontier AI lab like Anthropic or OpenAI, nor is it a traditional enterprise SaaS company. It’s AI infrastructure — the picks and shovels of the AI gold rush. Here’s how its median engineer compensation stacks up:

Scale’s $351K median is competitive for an infrastructure company but sits below the frontier AI labs. The gap narrows at senior levels — Scale’s L6 comp of $642K+ is within striking distance of Anthropic’s senior packages. The key differentiator is Scale’s equity profile: at $29B with $2B+ revenue and strong government contracts, the equity has more tangible value than many pre-revenue AI startups, even if the moonshot upside is smaller than frontier lab equity.

The Equity Story: $29B Valuation and Meta’s $14.3B Investment

Scale’s equity deserves its own section because it’s unusual. In early 2025, Meta invested approximately $14.3 billion for a 49% stake, pushing the valuation to $29 billion. This is a different animal from typical startup equity for several reasons:

• Revenue-backed valuation. Scale’s $2B+ revenue means the $29B valuation is roughly 14x revenue — aggressive but defensible for a high-growth AI infrastructure company. Compare this to pre-revenue AI startups where the valuation is entirely forward-looking.
• Strategic anchor investor. Meta’s 49% stake signals deep strategic alignment. Meta needs Scale’s data labeling infrastructure for its AI models (Llama family), which reduces downside risk — even in a market downturn, the Meta relationship provides a revenue floor.
• Government contracts. Scale’s work with the US Department of Defense and other government agencies provides revenue diversification that pure-AI startups lack. Government contracts are typically multi-year and sticky.
• Liquidity considerations. As a private company, Scale equity is not immediately liquid. However, the $29B valuation and Meta’s investment create a strong precedent for secondary market transactions, and the IPO path is plausible given the revenue scale.

For senior engineers receiving 40–50% of their comp in equity, the question isn’t whether Scale’s equity has value — it clearly does. The question is whether you believe Scale’s position as AI infrastructure (vs. building the models themselves) is durable. If AI labs increasingly build their own labeling and evaluation tools, Scale’s moat could narrow. If the market continues to need specialized data infrastructure at scale — which current trends strongly suggest — the equity upside is substantial.

Machine Learning & Research Compensation

ML engineers and research scientists at Scale have a somewhat different compensation profile than software engineers. Based on available data, ML engineer compensation ranges from approximately $195K at L3 to $254K at L4. This is notably lower than the software engineering track at the same levels.

The gap likely reflects two factors: (1) Scale’s ML engineering roles may be more applied/evaluation-focused than the pure research roles at frontier labs, and (2) the sample size for ML-specific roles is smaller, which can skew the data. For ML engineers evaluating Scale, the compensation is competitive with applied ML roles at enterprise companies but below what Anthropic, OpenAI, or Google DeepMind pay for comparable research-oriented positions.

What Employees Say About Compensation

Scale’s Glassdoor rating of 3.5/5.0 from 411 reviews is below the median for our directory. The 2.7 WLB score is one of the lowest we track, below even Cognition (3.2) and OpenAI (3.3). Only 56% of employees recommend working there. The compensation is a genuine bright spot — but the trade-off is intensity, organizational growing pains from rapid scaling, and management quality that varies significantly by team.

Glassdoor Ratings Breakdown

The culture and values score of 2.9 is the most concerning metric. It suggests that while the work is interesting and the pay is strong, the day-to-day experience of working at Scale doesn’t consistently match what employees expect. Reviews cite organizational churn from rapid scaling, contractor workforce dynamics that complicate team cohesion, and inconsistent management — particularly in non-engineering functions.

Is Scale AI Compensation Worth It?

The answer depends on what you’re optimizing for. Here’s how to think about it:

• If you want maximum cash comp: Scale’s $351K median is strong but not the highest. OpenAI and Anthropic pay more. Consider those if raw compensation is your top priority.
• If you want equity with real revenue backing: Scale’s $29B valuation is supported by $2B+ revenue, Meta’s strategic investment, and government contracts. This is more tangible than most startup equity — but less liquid than public company RSUs at Datadog or Palantir.
• If you want work-life balance: Look elsewhere. The 2.7 WLB score is a clear signal. Companies like Notion (4.2), Linear (4.4), or PostHog (4.5) offer strong comp with better balance.
• If you want to work on AI infrastructure at massive scale: Scale is one of the few companies where you’re building the data layer that powers the world’s largest AI models. The product impact is real and measurable. If that excites you, the compensation is competitive enough to make the trade-offs worthwhile.

Open Positions at Scale AI

Scale currently has 174 open positions, spanning engineering, product, sales, and operations. For the full list with culture context, visit the Scale AI culture profile.