Recruits Lab places bioinformaticians, computational biologists, scientific software engineers, and ML-bio engineers at venture-backed biotech, AI-bio, and platform companies. Average hire time: 14 days.
Bioinformatics talent sits in one of the most contested pools in tech and biotech. Every AI-bio company, every platform biotech, every large pharma target-discovery team, and every academic spinout is chasing the same 2,000 people who can actually build computational pipelines that drive real biology decisions.
Recruits Lab is a Bioinformatics recruiting firm for biotech, pharma, AI-bio, and platform biology companies. We place across the full spectrum: research bioinformaticians, computational biologists, scientific software engineers, ML-bio engineers, and Directors of Computational Biology.
We screen for the right blend. Some roles need deep biology with workable code. Some need deep engineering with workable biology. Some need real ML for genomics. Each profile has a different talent pool. We map the right one per search.
Most candidates we place hold a PhD in computational biology, bioinformatics, or biostatistics, or an MS in computer science with biotech industry experience. We source from competitor programs, top academic labs, and AI-bio startups that are downsizing.
Our subscription model fits full computational team builds. Our flat 20 percent contingency fits one-off senior hires. Every placement carries a 90-day replacement guarantee.
Why this market is hard to recruit for. And how we solve each one.
A research bioinformatician is not interchangeable with a scientific software engineer. We calibrate the blend.
Single-cell, bulk RNA, proteomics, imaging, and structural biology each require different tooling. We map on actual data experience.
Some roles need a candidate who can talk to wet-lab biologists daily. Some can ship in isolation. We screen on the right fit.
Top ML-bio engineers at well-funded AI-bio companies are at $300K-$500K total comp. We close on mission, science, and equity.
Strong computational biologists get aggressive counter-offers. We manage the resign conversation directly.
Computational candidates ask about compute budget and infrastructure. We surface compute strategy in the first call.
The repeatable system behind our 14-day average hire time.
Call covering data type, scientific question, tooling expectations, compute budget, and team composition.
Map of computational biologists from competitor programs, academic groups, and AI-bio startups.
Outreach that references the data, the scientific question, and the role of computation in driving program decisions.
5-8 finalists with publication summary, tooling history, and biology-engineering blend assessment.
We manage offers, equity translation, and start dates.
Directional 2026 U.S. base salary estimates for venture-backed companies. Excludes equity, bonus, and sign-on. Confirm with current market data before extending offers.
| Role | Base Salary Range |
|---|---|
| Bioinformatics Scientist | $160K–$210K |
| Senior Bioinformatics Scientist | $195K–$250K |
| Principal Bioinformatics Scientist | $240K–$310K |
| Scientific Software Engineer | $200K–$280K |
| ML Engineer (Genomics / Bio) | $240K–$340K |
| Director, Computational Biology | $300K–$420K |
Sources: Radford, Levels.fyi, Pave 2026 data and Recruits Lab placement benchmarks. AI-bio total comp can exceed these ranges materially. Directional only.
Quick answers to the questions founders and hiring leaders ask most.
Hiring a Bioinformatics Scientist requires matching data type (single-cell, bulk RNA, proteomics, imaging), scientific question, and compute strategy. Recruits Lab runs data-type-matched searches that close in 14-21 days.
A Bioinformatics Scientist in 2026 typically earns $160K–$210K base. Senior Bioinformatics Scientists run $195K–$250K. Directors of Computational Biology reach $300K–$420K. ML-bio engineers at well-funded AI-bio companies often exceed these ranges.
Bioinformatics typically emphasizes pipeline, tooling, and data engineering for biology. Computational Biology typically emphasizes hypothesis-driven analysis and model building. Many candidates overlap, but the dividing line shows up in code-vs-paper output ratio.
Yes. Single-cell, multi-omics, structural biology ML, and protein design candidates are within our active pool.
Needed two computational biologists with single-cell experience and one ML engineer with genomics deployment experience in one quarter.
Recruits Lab embedded a dedicated computational recruiter. Built parallel target maps across competitor AI-bio companies and top academic single-cell labs.
All three roles signed in 42 days. Platform v1 shipped one quarter ahead of plan.
"Recruits Lab actually knows the single-cell tooling landscape. Their outreach referenced specific datasets and methods."
"They placed three computational hires in one quarter on subscription for less than a single retained search would have cost."
Yes. ML-bio is one of our highest-velocity pools.
Yes. Large pharma target discovery, computational chemistry, and structural biology hires are within our practice.
Yes. Computational roles are often remote-friendly. We pre-qualify on geography.
90-day replacement guarantee on every placement.
Book a 30-minute computational hiring call using the CTA on this page.
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