Solutions
Hire vetted AI, ML and data engineers
Rigorously vetted, human-reviewed candidates for the roles that make or break an AI product — from ML engineers and data scientists to MLOps and AI platform engineers.
Who this is for
B2B SaaS teams shipping AI features, AI-native startups, and scaleups building an internal ML platform. If your search list includes any of the roles below, this page is for you.
Roles we hire for
- Machine Learning Engineers
- Data Scientists
- Applied Research / Applied AI Engineers
- MLOps and ML Platform Engineers
- Data Engineers (batch and streaming)
- Analytics Engineers
- AI Product Managers (on request)
What good looks like for an AI hire
Real production experience, not tutorials.
We screen for candidates who have shipped models to production and dealt with the boring parts — data quality, drift, latency, cost. Every candidate is reviewed by a person before you see them.
English strong enough for the actual work.
Assessed English proficiency for every candidate. AI work involves specification, debate, and writing — not just code.
Sourced for your hours.
Timezone-aligned — sourced for real overlap with your working hours, because AI teams pair-debug and ship fast.
How the search works
- Intake call — role, seniority, tech stack, timezone.
- Human-reviewed shortlist — typically three to five candidates, with a written summary and English assessment.
- Your interviews — you run your loop; we coordinate.
- Offer, contract, and Employer of Record onboarding where needed.
For the full flow, read how Scaleup365 works.
Engagement models
Choose the model that fits: recruitment for a specific hire, Remote Staff Augmentation for a curated bench under our management, or Employer of Record for compliant employment in supported countries.
What we do not claim
- No autonomous "AI matching" inside our own product — our process is human-first, software-supported.
- No percentage cost-savings numbers we cannot show the math on.
- No candidate pedigree ("FAANG", "YC") we cannot verify per candidate.
Tell us what you are shipping.
We will come back with a shortlist path. Or explore customer support, why teams choose us, or the full FAQ.