ML/AI Engineer | dbt Labs Global Negotiation Guide
Negotiation DNA: Balanced Equity + Bonus | Semantic Layer AI Expansion | Analytics Engineering Category Creator | Series D Growth-Stage Equity
| Region | Base Salary | Stock (Options/RSU/4yr) | Bonus | Total Comp |
|---|---|---|---|---|
| Philadelphia / Remote-US | $178K–$218K | $145K–$248K | 10–15% | $225K–$295K |
| San Francisco | $188K–$232K | $158K–$268K | 10–15% | $240K–$315K |
| London | £128K–£165K | £102K–£185K | 10–15% | £162K–£218K |
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dbt Labs ML/AI Engineers build the AI capabilities being integrated across the dbt platform — from LLM-powered SQL generation to intelligent transformation optimization to AI-driven data quality and the AI-enabled Semantic Layer. In February 2026, dbt Labs is aggressively hiring ML/AI engineers as the company expands from transformation tooling into AI-powered analytics engineering. This is the role that defines what AI means for the analytics engineering category.
ML/AI Engineers at dbt Labs are building at the intersection of two massive markets — analytics engineering and AI — with the unique advantage that every AI feature reaches tens of thousands of companies through the dbt ecosystem.
Level Mapping: dbt Labs ML/AI = Google L4 ML = Snowflake ML = Databricks ML = Amazon L5 Applied Scientist
🏗️ dbt Labs AI-Powered Analytics Lever
In February 2026, dbt Labs' AI strategy centers on making analytics engineering AI-native — using LLMs to generate transformations, AI to optimize query performance, and the Semantic Layer as the governed interface between enterprise data and AI agents. ML/AI Engineers are building the capabilities that define this new category.
Your AI features define what AI-powered analytics engineering means for the industry — every model you deploy into the dbt platform becomes the standard that 40,000+ companies use, creating category-defining impact.
Global Levers
- AI Category Definition: "I'm not just building features — I'm defining what AI-powered analytics engineering means for the industry. This category-defining work commands premium equity — $245K+ over 4 years."
- Platform-Scale AI Impact: "Every AI feature I build reaches 40,000+ companies using dbt. This platform-scale ML impact is exceptional and must be reflected in compensation."
- AI Startup Counter: "I have offers from AI startups with larger equity grants and significant upside potential. dbt Labs must make the equity competitive with the AI talent market."
- Semantic Layer + AI = Revenue: "The AI-enabled Semantic Layer is dbt Labs' premium enterprise monetization strategy. I build the ML capabilities that drive this revenue — direct monetization impact."
Negotiate Up Strategy: "I'd like equity at $248K over 4 years with a 13% target bonus. I'm building the AI capabilities that define analytics engineering's next era — reaching 40,000+ companies. I have AI startup offers with larger equity. dbt Labs equity must reflect both the category-defining impact and competitive AI market." Accept if above $225K equity.
Evidence & Sources
- [dbt Labs — AI Feature Integration Roadmap 2026]
- [dbt Labs ML/AI Comp — Levels.fyi 2025-2026]
- [Semantic Layer AI — Enterprise Monetization Strategy]
- [Analytics Engineering AI — Category Evolution 2026]
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