Side-by-Side Comparison
Open AI Roles
126
Salary Range
$104K - $428K
Top Roles
AI/ML Engineer, AI Software Engineer, AI Product Manager, Data Scientist
Top Skills
GcpPythonGeminiVertex AiTensorflow
% Remote
0.0%
Experience Mix
Mid 50%, Senior 50%
Company Stage
Unknown
Amazon Web Services
Open AI Roles
73
Salary Range
$82K - $342K
Top Roles
AI/ML Engineer, AI Product Manager, Research Scientist, Data Scientist
Top Skills
AwsBedrockPythonSagemakerRag
% Remote
0.0%
Experience Mix
Mid 45%, Senior 55%
Company Stage
Unknown
Who Wins?
Best for Salary
Google
Median ceiling ~$253K
Best for Remote
Google
0.0% remote positions
Most Roles Available
Google
126 open AI positions
Quick Verdict
For compensation, Google offers significantly higher pay, with median salary ceilings roughly 19% above Amazon Web Services. Both companies are actively hiring with a similar number of open AI roles (126 at Google vs 73 at Amazon Web Services).
Which Should You Choose?
Choose Google if you prioritize:
- higher compensation with median salary ceilings above the competition
- broader role variety across 8 different AI job categories
- more open positions (126 active AI roles)
- working with Gemini, Jax, Gcp
Choose Amazon Web Services if you want:
- working with Prompt Engineering, Claude, Golang
- its specific team culture and project focus
Career Considerations
Beyond headline salary numbers, consider what each company offers for long-term career growth. Since both companies lean toward onsite work, consider how each company's office locations align with your living situation and career network.
Frequently Asked Questions
Google currently shows higher median salary ceilings for AI positions. Google ranges around $104K - $428K while Amazon Web Services ranges around $82K - $342K. Keep in mind that posted salary ranges reflect base compensation and often exclude equity, signing bonuses, and annual performance bonuses that can add 10-30% to total compensation. Actual offers also depend on specific role, seniority level, location, and negotiation. Check individual job listings for the most current figures.
Google offers more remote opportunities at 0.0% of their AI roles. Google is at 0.0% remote while Amazon Web Services is at 0.0% remote. Remote availability can shift quickly as companies adjust return-to-office policies. Some roles listed as hybrid may allow mostly remote work in practice. If remote work is a priority, filter by the remote tag on individual company pages and pay attention to whether the listing specifies a geographic requirement.
Google focuses on AI/ML Engineer, AI Software Engineer roles, while Amazon Web Services emphasizes AI/ML Engineer, AI Product Manager. Skill requirements also differ: Google prioritizes Gcp, Python, Gemini, while Amazon Web Services looks for Aws, Bedrock, Python. These differences often reflect each company's core AI products and business model. The tech stack you work with early in your career shapes your trajectory, so consider which skill set aligns with your long-term goals.
Career growth depends on company stage, team size, and role scope. Google (Unknown) has 126 open AI roles, while Amazon Web Services (Unknown) has 73. Companies with more open roles often provide faster internal mobility and broader project exposure. Look at the experience mix breakdown above to gauge whether each company is primarily hiring senior talent or building entry-level pipelines, as this signals different mentorship and advancement cultures.
Data Source: Analysis based on 199 AI job postings collected and verified by AI Pulse. Data reflects active job listings as of July 2026. Salary figures represent posted compensation ranges and may not include equity, bonuses, or other benefits.
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