Salary Explorer
Real aggregated compensation by role, level and market — annual salary in thousands.
Markets: United States · United Kingdom · Singapore · Remote · Updated 2026-07-15
Whether you are benchmarking a machine learning engineer salary or comparing the broader AI engineer salary landscape, this page aggregates real compensation data for eight AI roles — from Machine Learning Engineer to LLM Engineer and AI Product Manager — broken down by seniority level and market. Every figure is an annual range with an average, so you see the full spread rather than a single median. In US data, entry-level ML engineers typically see base salaries from roughly $80k to $130k, while senior packages reach $200k–$350k.
Use the explorer below to compare roles across four markets — the United States, United Kingdom, Singapore and Remote — and to check P25–P90 percentiles, equity, bonus and contractor rates for each. The city section covers 15 global hubs with cost-of-living adjustments, because the same salary goes further in some markets than others. For levels, negotiation and total-comp strategy in depth, read our machine learning engineer salary guide.
Professionals with AI skills can earn 40-60% more than traditional roles
Salary ranking by market
Highest-level average for each role in United States (per year)
Compensation detail · by level & market
- United States$80k–130k · avg $105k
- United Kingdom£50k–80k · avg £65k
- SingaporeS$60k–100k · avg S$80k
- Remote$70k–110k · avg $90k
- United States$130k–200k · avg $165k
- United Kingdom£80k–120k · avg £100k
- SingaporeS$100k–150k · avg S$125k
- Remote$110k–170k · avg $140k
- United States$200k–350k · avg $275k
- United Kingdom£120k–200k · avg £160k
- SingaporeS$150k–250k · avg S$200k
- Remote$170k–300k · avg $235k
US salaries often include significant equity/stock options
Where to work · 15 global cities
ML Engineer salary, cost of living and visa outlook by city (salary in local $k/year).
Pick by priority
- Maximize Savings:Seattle, Austin, Berlin, Bangalore
- Maximize Learning:San Francisco, New York, London
- Most Opportunities:San Francisco, New York, Seattle
- Easiest Immigration:Toronto, Berlin, Sydney
- Best Work Life Balance:Berlin, Sydney, Toronto
Detailed compensation · percentiles & equity
P25–P90 base plus equity, bonus, sign-on and contractor rates (annual $k).
Visa & immigration
Work-visa routes compared — processing time, cost and approval rate.
- ✓Path to Green Card
- ✓Dual intent allowed
- ✓Can work only for sponsor
💡 Apply through multiple employers if possible
- ✓Predictable (points-based)
- ✓Direct to PR
- ✓No employer tie
- ✓Family included
💡 Max your points (French helps, age <30 better)
- ✓Fast
- ✓Cheap
- ✓No language requirement
- ✓EU access
- ✓Path to PR (21-33 months)
💡 Apply to jobs before moving
- ✓Fast processing
- ✓Path to settlement (5 years)
- ✓Family included
💡 Priority processing worth it (£500)
Quick comparison
- Easiest:Germany (EU Blue Card) - if you have job offer
- Fastest:Germany (2-4 months)
- Cheapest:Germany (~€300)
- Highest Salary:United States (but lottery)
- Recommendation:Try Canada Express Entry + Germany EU Blue Card simultaneously for best odds
- Highest Approval:Germany (90%+)
- Best For Direct Pr:Canada (6-12 months to PR)
Real negotiation case studies
Anonymized before/after outcomes and what moved the number.
Metadata
Case Studies
Lessons
- ›Having competing offer increased leverage significantly
- ›Don't anchor too low - they met in middle
- ›Equity negotiable at startups (less so at big tech)
- ›Domain expertise (backend) justified higher offer
Outcome
Background
Transition
Offers Received
Counter
Final Offer
Initial Offer
Initial Offer
Negotiation Process
Lessons
- ›PhD + publications = high leverage
- ›AI safety companies pay competitively
- ›Multiple offers essential for top comp
- ›Mission alignment can override comp
Outcome
Background
Offers Received
Counter
Final Offer
Initial Offer
Initial Offer
Negotiation Process
Lessons
- ›Viral project was key (proof of ability)
- ›No degree = harder (120 apps for 1 offer)
- ›Small startups more willing to overlook no degree
- ›First job is foot in door (comp improves fast)
- ›Limited leverage with only 1 offer
Outcome
Background
Offers Received
Counter
Final Offer
Initial Offer
Negotiation Process
Key Insights
Salary FAQ
Common questions about machine learning engineer pay, answered with the data on this page.
How much does a machine learning engineer make?
In the US data on this page, machine learning engineers typically earn roughly $80k–$130k at junior level (0–2 years), $130k–$200k at mid-level and $200k–$350k at senior level, with averages around $105k, $165k and $275k respectively. UK and Singapore packages run lower in nominal terms — the tables above show all four markets side by side. For a full breakdown by level, company type and negotiation stage, read our machine learning engineer salary guide.
How does an ML engineer's salary grow with experience?
Steeply, in the data on this page: US average base pay rises from about $105k at junior level to roughly $165k at mid-level and around $275k for senior engineers — more than doubling across the first five-plus years. The mid-to-senior step is the largest single jump, so closing high-leverage skill gaps early compounds. Newer LLM-adjacent roles follow a similar curve — see our prompt engineer salary guide for a concrete example.
Which markets and cities pay the most for AI roles?
The United States tops the ranking table above for every role, with Remote and Singapore also flagged as hot markets. Among the 15 cities compared below, US hubs post the highest nominal salaries, but the cost-of-living-adjusted figures narrow the gap considerably — check the after-cost-of-living number on each city card before deciding. Our AI salaries by city guide walks through the trade-offs.
What is the difference between base salary and total compensation?
The ranges in the tables above are base salary. As the note on this page points out, US packages often add significant equity on top, plus annual bonus and sign-on — the percentile cards quantify each component per role and city, and total comp can run well above base at senior levels. For company-by-company packages broken down by level, try the company pay explorer.
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