Artificial intelligence continues to be one of the highest-paying fields in tech. But how much can you actually earn? This comprehensive guide breaks down AI salaries by role, experience level, location, and company type — with real data from 2026.
ML Engineer (Avg)
Data Scientist (Avg)
AI Research Scientist
MLOps Engineer
Machine Learning Engineer Salaries
Machine learning engineers are among the highest-paid technical roles. They combine software engineering skills with ML expertise to build production systems.
| Experience Level | US Average | Silicon Valley | Remote |
|---|---|---|---|
| Junior (0-2 years) | $105,000 | $130,000 | $85,000 |
| Mid-Level (2-5 years) | $145,000 | $180,000 | $120,000 |
| Senior (5-8 years) | $185,000 | $230,000 | $160,000 |
| Staff/Principal (8+ years) | $230,000+ | $300,000+ | $200,000+ |
💡 Key Insight
At FAANG companies (Meta, Apple, Amazon, Netflix, Google), total compensation including stock can be 50-100% higher than base salary. A senior ML engineer at Google might earn $250K base + $200K+ in stock annually.
Data Scientist Salaries
Data scientists focus more on analysis, experimentation, and insights. While slightly lower than ML engineers, compensation is still excellent.
| Experience Level | US Average | Top Companies |
|---|---|---|
| Junior (0-2 years) | $90,000 | $115,000 |
| Mid-Level (2-5 years) | $125,000 | $160,000 |
| Senior (5+ years) | $165,000 | $210,000 |
AI Research Scientist Salaries
Research scientists typically have PhDs and work on advancing the state of AI. These are among the highest-paid roles in tech.
| Company Type | Base Salary | Total Comp (w/ Stock) |
|---|---|---|
| Academia | $100,000 - $180,000 | Same (no stock) |
| Startups | $150,000 - $220,000 | $200,000 - $400,000 |
| Big Tech | $180,000 - $280,000 | $350,000 - $600,000+ |
| OpenAI, Anthropic, DeepMind | $250,000 - $400,000 | $500,000 - $1M+ |
Emerging Roles: New AI Careers
Prompt Engineer
A new role focused on optimizing interactions with large language models.
- Entry level: $80,000 - $120,000
- Experienced: $150,000 - $200,000
AI Safety Engineer
Ensures AI systems are safe, aligned, and robust.
- Average: $160,000 - $250,000
- Top labs: $300,000+
LLM Engineer
Specializes in fine-tuning and deploying large language models.
- Average: $150,000 - $220,000
Salary by Location
| Location | ML Engineer Avg | Cost of Living Adjusted |
|---|---|---|
| San Francisco Bay Area | $195,000 | $130,000 equivalent |
| New York City | $175,000 | $125,000 equivalent |
| Seattle | $170,000 | $135,000 equivalent |
| Austin | $150,000 | $140,000 equivalent |
| Remote (US-based) | $145,000 | Varies by location |
| UK (London) | £85,000 (~$105,000) | $90,000 equivalent |
| Germany | €75,000 (~$80,000) | $85,000 equivalent |
💡 Remote Work Advantage
Many AI professionals are maximizing earnings by working remotely for US companies while living in lower cost-of-living areas. A $150K remote salary goes much further in Austin or Denver than in San Francisco.
How to Maximize Your AI Salary
- Specialize in high-demand areas: LLMs, computer vision, and MLOps command premium salaries
- Build a strong portfolio: Demonstrable projects can add 10-20% to offers
- Negotiate: AI talent is scarce — companies expect negotiation
- Consider total compensation: Stock options at the right company can double your earnings
- Stay current: Skills in the latest frameworks (PyTorch, LangChain) are valued
Salary Negotiation Tips
AI roles have significant room for negotiation. Here's how to maximize your offer:
- Always get competing offers — this is your strongest leverage
- Research ranges on levels.fyi and Glassdoor
- Negotiate base, stock, and signing bonus separately
- Ask for more stock if base is capped
- Don't reveal your current salary (illegal to ask in many states)
Conclusion
AI careers offer some of the highest salaries in tech, with significant room for growth. Whether you're just starting out or looking to level up, investing in AI skills consistently pays off.
The key is to combine technical expertise with practical experience. Build projects, contribute to open source, and stay current with the rapidly evolving field. The opportunities — and compensation — will follow.