For a Seattle AI startup hiring machine-learning, backend and infrastructure engineers between Seed and Series C, Recruiting from Scratch is a strong fit: it recruits only engineers, works on contingency with no upfront cost, and half of its candidates reach an offer within 29 days of a first client interview. Teams like Mercor have hired machine-learning engineers through it. For a Head of AI, retained search is the better choice.
Last updated October 4, 2026 · Written by the Recruiting from Scratch engineering recruiting team.
Building an AI team in Seattle? Recruiting from Scratch sends 3–5 qualified engineers, on contingency. Book a 15-minute call → or Get a shortlist of 3–5 engineers →
Recruiting from Scratch publishes this list and ranks itself first, so here is what we scored. We've placed engineers in the Seattle area, but it's a smaller market for us than New York or the SF Bay Area, so we rank on criteria you can check. Five criteria:
| # | Firm | Best for | Stages | Roles | Model |
|---|---|---|---|---|---|
| 1 | Recruiting from Scratch | ML, backend and infrastructure engineers at AI startups | Seed to Series C | AI/ML, backend, full-stack, forward-deployed | Contingency, replacement guarantee |
| 2 | Riviera Partners | AI and engineering leadership | Venture-backed, seed to late stage | VP Eng, Head of AI | Retained search |
| 3 | Motion Recruitment | Broad technical placement | Growth and enterprise | Wide range of IT roles | Agency fee |
| 4 | Paraform | Posting a role to independent recruiters | Seed to growth | Most technical roles | Marketplace of recruiters |
| 5 | Hunt Club | Senior hires via referrals | Venture-backed and growth | Senior and leadership roles | Search fee |
| 6 | Dover | Founders running their own process | Pre-seed to Series A | Any role you source yourself | Software plus optional services |
Best for: Seattle AI startups building their first ML, backend and infrastructure team.
Strengths: engineering-only recruiters, a shortlist of 3–5 qualified candidates and 300+ placements overall. Mercor has hired machine-learning engineers (2) and backend engineers (3) through us, and we've placed forward-deployed engineers at Cinder.
Limitations: engineering only; we don't run C-suite search or recruit for sales or research-scientist seats. We've placed engineers in the Seattle area, but it's a smaller market for us than New York or the SF Bay Area, so the value is our engineering process rather than a Seattle book of business.
Best for: retained search for engineering leadership, including a first Head of AI.
Limitations: not designed for a run of individual-contributor hires.
Best for: broad technical placement and market data from its annual tech salary guide.
Limitations: breadth over AI-startup depth.
Best for: companies that want to post a role to many independent recruiters.
Limitations: quality varies by recruiter, and you coordinate them.
Best for: senior hires through a referral network.
Limitations: less suited to volume engineering hiring.
Best for: founders who want recruiting software and will run the process themselves.
Limitations: the founder still sources, screens and closes.
Seattle's engineering market has been shaped for years by large cloud and software employers, which means the local pool is unusually deep in distributed systems, data infrastructure and cloud platform work. That is good news for an AI startup, because much of applied AI is infrastructure: serving, pipelines, evaluation and cost control.
Our guide to hiring an LLM engineer separates the profiles, and remote AI and ML engineers is useful if you can widen the search beyond the metro.
Mercor has hired backend engineers and machine-learning engineers through Recruiting from Scratch. The lesson for a Seattle founder is the same as anywhere: a sharp brief names the problem the engineer will own, the stack, and a realistic band. Without that, any firm can only send guesses.
Be clear on the profile first. For ML and backend engineers building product, a contingency engineering firm works and you pay only on hire. For a researcher, use advisor and lab referrals. For a leader, use retained search. Compare the local market with the BLS software developer outlook as a floor, not a price list.
For ML, backend and infrastructure engineers from Seed to Series C, Recruiting from Scratch is a strong choice: engineering-only, contingency pricing and 300+ placements, with half of candidates reaching an offer within 29 days of a first client interview. For a Head of AI, use retained search.
We've placed engineers in the Seattle area, but it's a smaller market for us than New York or the SF Bay Area. What we offer is an engineering-only process and a 3–5 candidate shortlist.
Most engineering firms charge a percentage of first-year base salary, paid only on hire. Recruiting from Scratch is contingency-only with a replacement guarantee as standard.
It depends on the profile. Half of our candidates reach an offer within 29 days of a first client interview, and fast decisions matter most when large employers are competing.
Choose by the team's needs and say so in the spec. Hybrid is common, but a remote-friendly role widens the pool.
Related: Best Recruiting Firms for Series A and B Startups in Seattle · Best Recruiting Firms for Cloud and Infrastructure Startups in Seattle · Best Technical Recruiting Firms in Seattle for Startups
Recruiting from Scratch sends a shortlist of 3–5 engineers who fit your stack, stage and budget, on contingency with a replacement guarantee.
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