About this job
<p style="min-height:1.5em"><strong>Adaptyv is building an automated lab that lets AI agents run biology experiments. </strong></p><p style="min-height:1.5em">We're entering the era of agentic science where AI models can now design novel proteins, propose hypotheses, and iterate on experimental results. But they can't run the experiments themselves - that's still a manual, months-long process. We're building the infrastructure that gives AI agents access to the physical world.</p><p style="min-height:1.5em">We are one of the fastest growing biotech companies, trusted by leading biopharmas, frontier AI labs, and the techbio companies pushing the field forward. This is a rare chance to help advance some of the most important work happening in biotech today.</p><p style="min-height:1.5em">Our automated lab is powered by a deep software + hardware stack: lab instruments worth millions of USD reverse-engineered into API-controllable hardware, dozens of devices orchestrated through complex workflows, full observability on everything that happens in the lab, processing pipelines for messy physical-world data, and AI systems that troubleshoot production results and accelerate assay development.</p><p style="min-height:1.5em">We’re growing rapidly and are hiring for talented people to scale and support the massive demand for AI-driven wet lab experimentation.</p><h2>About the Role</h2><p style="min-height:1.5em">You are here to scale up data generation. Design teams can hand us 10⁶ sequences, and our automated infrastructure measures on the order of 10³ of them individually. Library construction and display is what closes that gap.</p><p style="min-height:1.5em">We want someone who has set these systems up before and can do it again here, with their own hands. Phage, ribosome, mRNA, yeast, cell-free: which one fits depends on the library and the target, and part of the job is making that call and then building it rather than writing a recommendation.</p><p style="min-height:1.5em">This is a build role, not a service role. For your first months you are making libraries, running selections, working out why a round collapsed, and turning what works into something the automation team can run without you.</p><h2>What You'll Do</h2><ul style="min-height:1.5em"><li><p style="min-height:1.5em"><strong>Build the libraries.</strong> Oligo pools, combinatorial assembly, barcoding. More campaigns fail here than at selection.</p></li><li><p style="min-height:1.5em"><strong>Run selections end to end</strong>, including the call on whether a round enriched real binders or just fast growers.</p></li><li><p style="min-height:1.5em"><strong>Pick the platform per campaign and stand it up.</strong> Based on the library and the target, not on what you happened to use last.</p></li><li><p style="min-height:1.5em"><strong>Own the sequencing analysis.</strong> You don't need to be a bioinformatician, but you can't be waiting on one.</p></li><li><p style="min-height:1.5em"><strong>Hand off to automation.</strong> A protocol that only works when you personally run it isn't finished.</p></li><li><p style="min-height:1.5em"><strong>Close the loop.</strong> Selected designs get expressed and measured on BLI and SPR by the team next door. That tells you whether the selection worked.</p></li></ul><h2>What We're Looking For</h2><ul style="min-height:1.5em"><li><p style="min-height:1.5em"><strong>MSc / PhD in molecular biology, protein engineering, or a relevant field, plus 3+ years running display and selection yourself.</strong></p></li><li><p style="min-height:1.5em"><strong>You have set up a display platform, not just used one. This is the core requirement.</strong> Built the library, got the selection working, and produced binders that held up in an independent assay. Managing outsourced CRO campaigns is not the same thing.</p></li><li><p style="min-height:1.5em"><strong>Depth in at least one display format and working literacy across the rest.</strong> We are not fixed on which one.</p></li><li><p style="min-height:1.5em"><strong>High-diversity cloning</strong>, and an understanding of where bias enters a pool and what it costs you later.</p></li><li><p style="min-height:1.5em"><strong>NGS as a routine tool</strong>, and FACS if you have it.</p></li><li><p style="min-height:1.5em"><strong>Enough Python or R to analyze your own data</strong> without joining a queue.</p></li><li><p style="min-height:1.5em"><strong>You use AI tools seriously.</strong> It's 2026 and we run on Claude Code across the company. You also need the judgment to check what comes back.</p></li><li><p style="min-height:1.5em"><strong>A self-starter.</strong> Nobody is going to hand you a prioritized queue. You decide what to build, build it, and tell us what you learned.</p></li><li><p style="min-height:1.5em"><strong>Startup speed, not academic pace.</strong> Campaigns run against customer deadlines. A working platform with known limits beats an elegant one next year.</p></li><li><p style="min-height:1.5em"><strong>You want your protocols automated</strong> rather than manual forever.</p></li></ul><p style="min-height:1.5em">If your instinct is that a campaign is finished once you have ten good clones, we will frustrate each other. We want data, not a hit list.</p><h2>Details</h2><ul style="min-height:1.5em"><li><p style="min-height:1.5em"><strong>Location:</strong> Lausanne, Switzerland (on-site)</p></li><li><p style="min-height:1.5em"><strong>Type:</strong> Full time</p></li><li><p style="min-height:1.5em"><strong>Start date:</strong> ASAP</p></li></ul><p style="min-height:1.5em"></p><p style="min-height:1.5em"><strong>Application deadline</strong></p><p style="min-height:1.5em">We are reviewing applicants on a rolling basis.</p><p>Find more <a href="https://www.arbeitnow.ch/english-speaking-jobs">English Speaking Jobs in Switzerland</a> on Arbeitnow</a>