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AI talent is the most competitive hiring market in history. We find the engineers, researchers, and product leaders who can actually ship AI products.
"We interviewed 47 'machine learning engineers.' Only 3 could actually deploy a model to production without hand-holding."
— Sarah Chen, CTO at DataFlow AI
We've spent 3 years building relationships with AI talent who can actually ship products. Not just researchers. Not just theorists. People who build things.
PhD researchers from top universities who've made the jump to industry and can translate research into products.
Senior engineers from Google, Facebook, Microsoft, and OpenAI who want to build the next generation of AI companies.
People who've already built AI startups and understand the challenges of going from 0 to product-market fit.
Anyone can claim to be an AI expert. We dig deeper to find people who can actually ship AI products.
Architecture discussions, model selection reasoning, deployment trade-offs, performance optimization.
Real projects, production systems, measurable business impact, not just Kaggle competitions.
Understanding of AI limitations, cost considerations, product implications, stakeholder communication.
Startup mentality, ability to work with ambiguity, collaboration skills, learning agility.
Series A Computer Vision
Needed Senior ML Engineer with production computer vision experience. Found ex-Tesla Autopilot engineer who built their entire detection pipeline.
Hired in 3 weeks
vs 8 months previous search
Series B Financial Services
Required Head of AI with both deep technical skills and ability to work with financial regulators. Placed ex-Goldman ML leader.
40% faster deployment
of ML models to production
Series A Medical Devices
Needed AI Product Manager who understood FDA regulations for medical AI. Found ex-Philips product leader with regulatory experience.
FDA approval
achieved 6 months early
AI salaries are high, but the right hire pays for themselves quickly. Here's what you should expect to pay in 2025:
Note: These are base salary ranges. Total compensation including equity can be 50-100% higher at well-funded startups. Geographic location, company stage, and candidate quality significantly impact final offers.
We ask for specific technical details: model architectures used, deployment challenges faced, performance metrics achieved, and business problems solved. We can quickly tell the difference between someone who's built production AI systems and someone who's just read papers.
Yes, but not on pure compensation. Startups win by offering: meaningful equity, faster career progression, opportunity to build from scratch, less bureaucracy, and direct impact on product decisions. We help position these advantages effectively.
For specialized roles, expect 4-8 weeks to present qualified candidates, then 2-4 weeks for interviews and offers. AI hiring moves faster than traditional tech recruiting because both candidates and companies know the market is competitive.
Yes - we help design technical evaluations that actually test for production AI skills, not just academic knowledge. Plus we provide interview preparation coaching for candidates to ensure they show up ready.
Stop competing with Google and OpenAI for talent. Find AI professionals who want to build the next generation of AI companies.