Wondering why one AI engineer wants $180k… and the next wants $280k? Trying to decide whether remote hiring still saves money in 2026? Not sure whether your salary bands are competitive or quietly killing your hiring velocity? Or whether “market rate” even exists anymore in AI engineering?

The no-hype salary benchmark report from MRJ

Trying to make sense of AI salary inflation in the US?

• Wondering why one AI engineer wants $180k… and the next wants $280k?
• Trying to decide whether remote hiring still saves money in 2026?
• Not sure whether your salary bands are competitive or quietly killing your hiring velocity?
• Or whether “market rate” even exists anymore in AI engineering?

You’re not alone. Every roadmap now depends on AI capability. Every funding deck talks about building internal AI teams. But ask ten CTOs what a competitive salary looks like and you’ll get ten different answers.

Some companies are still anchored to pre-AI software benchmarks.
Others are benchmarking against Big Tech packages they can’t realistically compete with.
A growing number only discover the gap after months of rejected offers and stalled delivery.

The result is slow hiring, missed product milestones, rising internal pressure and an invisible cost most teams underestimate: vacancy drag.

Our latest report breaks this down.

Built from live placement data, offer feedback and daily conversations with founders across New York, the Bay Area, Austin and Boston, it shows what AI engineers are actually being paid in 2026, how regional competition really works, and how to price roles accurately without burning runway.

Why this report matters

The US technology market is entering what we call the Great Recalibration.

The era of speculative hype hiring has ended. In its place is a more disciplined, data-driven approach to building production-ready AI teams. Investors want efficiency. Boards want predictable delivery. Engineering leaders are being judged on real output, not experiments.

At the same time, demand for applied AI capability continues to outstrip supply.

In 2026:

• The national senior median AI base salary is $230,625.
• Zone 1 Machine Learning Engineers now reach $270,000 base in hyper-competitive hubs.
• Zone 3 markets such as Austin and Boston standardise around $222,500, offering a scalable alternative for mid-sized companies.

Our internal data shows that companies failing to meet the $200k base floor for senior AI talent face an average time-to-fill of 114 days. For a 10 - 00 person organisation, that delay compounds quickly into missed delivery targets, lost momentum and frustrated teams.

This report exists to help leaders avoid those mistakes.

Not based on generic salary surveys.
Not based on outdated software benchmarks.
But based on what candidates are actually accepting in today’s market.

Specialist recruiter insight

“We’re seeing founders consistently underestimate how permanent the AI premium has become. The biggest hiring failures in 2025 weren’t talent quality issues, they were pricing mistakes. Teams either anchored to old software benchmarks or assumed remote hiring would suppress salaries. Neither assumption holds anymore.” - MRJ Consultant

That’s the reality MRJ sees every day across US growth markets.

The strongest hiring teams understand how compensation now varies by competitive zone, how Applied AI and Machine Learning roles price differently, and how remote hiring has effectively created a national pay floor rather than a discount.

What’s inside the report

1. The real salary split between Applied AI and Machine Learning roles
   Why product-focused Applied AI Engineers and core ML Engineers now command different salary bands, and how that affects workforce planning.
2. National salary benchmarks by seniority
   Clear base salary ranges from junior through staff level, including the current national senior midpoint of $230,625.
3. The four competitive market zones explained
   How Zone 1 hyper-hubs, Zone 2 premium centres, Zone 3 high-growth hubs and Zone 4 efficiency markets shape salary expectations and hiring strategy.
4. Remote pay is now a national benchmark
   Why remote AI roles are increasingly anchored to Zone 3 pricing rather than local cost-of-living models.
5. Two-year market movement: from plateau to production reality
   How the market shifted from stabilisation in 2024 to agentic acceleration in 2025 and sustained salary growth in 2026.
6. The real cost of misalignment
   A live case study showing how under-benchmarking delayed delivery and how correcting salary strategy unlocked rapid hiring.

Who this report is for

This report is designed for:

• CTOs, VPs of Engineering and Technical Founders
• Heads of Talent, HR Directors and Workforce Planners
• Startup and scale-up leaders building AI teams between 10–100 employees
• Operators responsible for budget ownership, hiring velocity and delivery risk

If you influence hiring strategy, compensation planning or delivery timelines, this report is built for you.

Why download it

This isn’t another generic salary snapshot or trend piece. It’s a recruiter-led, real-market view of what AI compensation actually looks like in the US right now.

You’ll come away with:

• A clear understanding of national and regional AI salary expectations
• Confidence in how to price roles by zone and seniority
• Practical insight into remote salary strategy
• Clarity on which skills justify genuine salary premiums
• Reduced risk of extended vacancies and failed hiring cycles

Download your copy and stop guessing what competitive AI compensation looks like in 2026. Build offers that close, not offers that stall.

Further reading from MRJ

What Does “Learning AI” Actually Mean? A No-Nonsense Guide for Tech Professionals

Is Product Management Becoming Product Engineering? How AI is Reshaping Roles in Big Tech

Advice on Future-Proofing Your Skillset

The Ultimate Interview Prep Guide for Product Managers

FAQs

Is this report only relevant for Silicon Valley companies?
No. The report covers national benchmarks, four competitive zones and remote hiring dynamics across the entire US market.

Does this include equity and total compensation?
The focus is on base salary, reflecting the growing shift toward guaranteed cash compensation in AI hiring.

Is this useful for early-stage startups?
Yes. Mispricing risk is highest in sub-100 headcount companies without strong internal benchmark data.

Can MRJ provide custom benchmarks for specific cities or sectors?
Yes. MRJ delivers hyper-local salary intelligence based on live placement and offer data. Please ask us more information.

About MRJ Recruitment

MRJ connects exceptional Product, Data, and Engineering talent with high-growth technology businesses across the US, UK, and Europe.

Our consultants operate at the intersection of hiring data, real-world placement intelligence, and market strategy, helping founders and leaders build teams that scale sustainably in competitive talent markets.