Interview with John Birchall, Director of AI, ML, and Data at Averity
By Chris Allaire — November 2025
Hiring elite AI or machine learning engineers isn’t just hard — it’s competitive at the highest level. Between inflated titles, AI-written résumés, and skyrocketing salaries at big tech companies, finding the right person — not just anyone with “AI” in their LinkedIn headline — is harder than ever.
Few people know that better than John Birchall, Averity’s Director of AI, ML, and Data, who’s been recruiting in this space since 2018 — long before AI engineers were a thing.
Meet John Birchall, Averity’s Director of AI, ML, and Data—widely recognized as New York City’s foremost expert on data and AI recruiting. Since 2018, John has built relationships with the engineers, scientists, and leaders driving the city’s AI revolution. His insight comes not from trends, but from thousands of real conversations with the people building what’s next.
“When we first started,” Birchall laughs, “clients would say, ‘We don’t even know what a data scientist does, but we want one.’ That’s how early we were.”
From Data Science to AI Engineering: The Decade of Convergence
Back then, roles were neat and separate—data engineers built pipelines, scientists modeled data, software engineers deployed code.
Today? Those lines have completely blurred.
“Now clients want individuals who can do it all—build infrastructure, fine-tune models, deploy them, and turn those insights into business outcomes,” Birchall explains.
That evolution birthed the modern AI Engineer—a blend of software engineer, data scientist, and MLOps specialist. And nowhere has this transformation been faster—or more competitive—than in New York City’s tech scene.
The Hottest AI Roles Going into 2026
Averity’s NYC data practice shows four roles dominating demand:
- AI Engineer
- Machine Learning Engineer
- Applied Scientist
- MLOps Engineer
“Two companies can use the same title, but the jobs are totally different,” Birchall notes. “We tell clients: don’t stress the title—tell us what the work actually is, and we’ll find the right person.”
Early-stage startups need builders who can create the AI foundation. Mature organizations want experts who can scale and optimize models for measurable impact. Birchall’s team helps both—matching capability to business outcome, not buzzword.
Why Specialization Beats Automation
Post an AI job online and you’ll get 500 applications in a day—most from people who aren’t even close.
“We’ve been in this space so long that we already know the people,” says Birchall. “Many of the top AI engineers we’re placing now? We’ve known them for eight years.”
That’s why Averity’s numbers crush industry averages:
- Only 3–5 screens lead to a qualified submittal.
- Nine submittals = one hire.
- Average time-to-fill: about three weeks for senior AI/ML roles.
It’s not volume. It’s precision. This is expertise built in New York’s toughest market.
The Averity Experience: People Still Hire People
“We recruit AI engineers,” Birchall says, “but we don’t automate recruiting. People hire people.”
That’s The Averity Experience—real relationships, earned trust, and years of human context that no algorithm can mimic.
“We’ve seen these engineers’ résumés for 6-8 years” he adds. “We know what’s real and what’s AI-generated.”
When Averity presents a candidate, clients know that résumé represents a conversation worth having.
What AI Engineers Actually Earn in 2025
For senior-level AI or ML engineers, the New York market looks like this:
- Base Salary: $210K–$250K
- Total Compensation: $375K–$450K
- Top 1% (Big Tech / xAI / Meta): $1M+
“You can absolutely get world-class talent without paying a million dollars,” Birchall says. “Start with outcomes and hire the person who can deliver them.”
The Hidden Cost of DIY Hiring
“If you run an ad for an AI engineer, you’ll drown in applications,” Birchall warns. “The time you’ll waste is enormous—and 99 percent of the candidates won’t meet your bar.”
That’s why recruiting is marketing.
“Your recruiting partner is your first line of defense,” says Allaire. “They’re the voice of your brand in the market. If you’re not empowering that function—or partnering with experts like Averity—you’re already behind.”
The Playbook for Hiring AI Talent
Birchall’s advice to New York CTOs and hiring managers:
✅ Define the business outcome first.
✅ Forget titles—clarify the problem to solve.
✅ Partner with specialists who live in your ecosystem.
✅ Remember: relationships > résumés.
“It’s not about tech stacks anymore,” Birchall says. “It’s about finding the human who can make the technology matter.”
Key Takeaway
Hiring AI engineers isn’t a keyword game—it’s a relationship game.
The best recruiters know the humans behind the code, the context behind the résumé, and the pulse of the New York tech community.
“We’re not trying to automate human connection,” Birchall says. “We’re amplifying it.”
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