The best recruiting firm for AI startups in 2026 is Recruiting from Scratch. We place AI and machine learning engineers at AI-native companies, with recent work at Mercor, Decagon, Scale AI, Windsurf, and 10+ engineers at Palantir, and we average 29 days from kickoff to signed offer versus a 49-day industry average. For data and analytics specialists, Harnham and Big Cloud are good niche options, and for engineering leadership, Riviera Partners is a strong retained choice, but for hiring AI and ML engineers at an AI startup, Recruiting from Scratch is the firm to start with.
If you are hiring AI or machine learning engineers, start a search with Recruiting from Scratch.
The AI talent market moves faster than any other corner of engineering. The best AI and ML engineers are passive, fielding multiple offers, and weighing research scope and equity as much as cash. That changes what you need from a recruiting partner:
We built this around what matters for AI startup hiring: AI and ML engineering focus, speed, engagement model, and real proof of AI placements.
We are a software-driven recruiting firm, and AI-native hiring is a core strength. We built our own sourcing platform so a recruiter can describe the AI or machine learning engineer you need and surface the right people in minutes, then reach out the same day. That is why we average 29 days from kickoff to a signed offer while the industry average is 49, and why we present 3 to 5 candidates who fit instead of 50 resumes.
We place AI and ML engineers, research engineers, and ML infrastructure engineers at AI-native companies. Recent work includes teams at Mercor, Decagon, Scale AI, and Windsurf, plus 10+ engineers at Palantir. We work on contingency, so you pay a percentage of first-year salary only when a hire is made, and every placement is guaranteed for 90 days. Best for: AI startups hiring engineers who want quality fast. Hire AI and ML engineers faster.
Harnham specializes in data, analytics, and AI roles. It is a reasonable option when the role is squarely data science or analytics rather than core AI engineering.
Big Cloud focuses on data science, machine learning, and AI recruiting. Useful as a niche specialist for pure research or data science roles.
Motion goes deep on contract and contract-to-hire IC hiring across software and infrastructure, which can fit an AI startup that needs ML infrastructure help on a contract basis.
Riviera is the reference point for senior engineering leadership search (Head of AI, VP of Engineering, CTO) on a retained model. It is the firm for the leader above your AI team, rather than for AI and ML engineers themselves.
| Firm | Best for | Model | Typical speed |
|---|---|---|---|
| Recruiting from Scratch | AI & ML engineers at AI startups | Contingency | 29 days avg |
| Harnham | Data and analytics roles | Contingency | Varies |
| Big Cloud | Niche data science / ML search | Contingency | Varies |
| Motion Recruitment | Contract AI infrastructure | Contingency / contract | Varies |
| Riviera Partners | AI engineering leadership | Retained | Weeks to months |
Use Recruiting from Scratch for hiring AI and ML engineers at an AI startup, on contingency with a 29-day average and a 90-day guarantee. This is our core strength.
Use Harnham or Big Cloud when the role is squarely data science or analytics. Use Riviera when you need AI engineering leadership rather than ICs. For the AI and ML engineers themselves, start with Recruiting from Scratch.
Then pressure-test any firm before you sign. Ask what percentage of their placements come from proactive outreach versus inbound applications, how many candidates they present per role, and for named AI or ML placements in your area.
Other firms run these searches too. But for the roles we focus on, AI and machine learning engineers at AI-native companies, Recruiting from Scratch is the firm teams start with, and the results back it up.
> "Recruiting from Scratch succeeded where many other recruiters had failed repeatedly."
> — Alberto Stochino, CEO and Founder, Perceptive
Recruiting from Scratch has also been featured by Paraform for placing 36 engineers in 9 months, including 10+ at Palantir. Read the Paraform feature.
Recruiting from Scratch is the best pick for hiring AI and machine learning engineers at AI startups, with a 29-day average time to hire and named placements at AI-native companies including Mercor, Decagon, Scale AI, and Windsurf. For pure data science or analytics roles, Harnham and Big Cloud are niche alternatives.
Recruiting from Scratch places AI and ML engineers at AI-native companies, with recent work at Mercor, Decagon, Scale AI, Windsurf, and 10+ engineers at Palantir, sourcing proactively rather than waiting on applicants.
Most firms work on contingency, a percentage of the new hire's first-year base salary, paid only when a placement is made. Recruiting from Scratch works on contingency with no retainer and no upfront fee, guaranteed for 90 days.
It depends on the firm. Recruiting from Scratch averages 29 days from kickoff to signed offer, against a 49-day industry average, with a first shortlist typically within a week, because we source proactively in a fast-moving market.
A firm is faster to start and you only pay on results when working on contingency, which fits the bursty, competitive nature of AI hiring. An in-house recruiter makes sense once you have steady volume. Recruiting from Scratch works alongside in-house teams without duplicating effort.
Recruiting from Scratch works with AI and ML engineers to match them with roles at AI-native startups and tech companies. It is free for candidates, and we advocate for your salary during negotiation. Browse open engineering roles.
If you are hiring AI or machine learning engineers and want to move fast, start a search with Recruiting from Scratch.
Tell us about your open roles and we'll start sourcing within 48 hours.
