PHASE 2 · JAN TO MAR 2027

• Workcells arrive in the lab. Move the validated assays onto them, running with instrumentation and human intervention in the loop. Validate equivalence against your manual baselines and triage failures.
• Open the assay menu to customers through manual and semi-automated services. Run real experiments for real customers.
• Help bring on the next scientists and lab technicians as the vertical grows.

Who you are

You are a protein scientist who is excited about the actual work: designing, running, and validating at the bench. You are comfortable in the details. You have hands-on experience with high throughput, plate-based methods across molecular biology, protein expression, purification, and QC. The shape of the problem is what attracts you: assays designed for autonomous execution from day one, in a business where the data the lab produces is itself the product.

You write good SOPs, and you hold yourself and your colleagues to clear reproducibility thresholds. You are pragmatic about being hands-on in the early phase, when the cadence is heaviest, and you understand it eases as protocols move onto instrumentation. You enjoy working at the boundary with non-biologist colleagues (automation engineers, software engineers, AI researchers), and you do not require them to be scientifically fluent before you will collaborate.

This role is open at Scientist and Senior Scientist level. The work is hands-on bench science at both, with collaboration into automation and software; the difference is depth of ownership, design authority, and how much of the team you help build. We do not hire people into boxes, and the early team stretches beyond the strict edges of any role.

MUST HAVE

• Comfortable handling DNA design and linear and plasmid DNA production at high throughput, expressing proteins, and purifying them with QC steps for validation, executing protocols at the bench through manual, semi-automated, and instrumented phases.
• Core experience within biologics.
• A track record of working alongside non-scientist colleagues (automation, software, computational) on a shared workflow.
• A PhD in protein biochemistry, molecular or structural biology, biophysics, analytical characterisation, or biologics developability, with two or more years of relevant hands-on experience; or a relevant science MSc with five or more years of equivalent bench experience in protein science.
• Independent, hands-on competence across protein science: molecular biology (DNA production with Gibson and Golden Gate assembly at transfection-grade quality), protein expression (cell-free, IVTT, E. coli and mammalian), and protein purification (automated magnetic-bead workflows), with exposure to at least one of these at high throughput (24, 96, and 384-well plate formats). Protein characterisation across at least two core biophysical methods (for example CE-SDS, DLS, nanoDSF/DSF, analytical SEC, HIC, or LC-MS intact mass analysis).
• Confident data analysis, including telling instrument artefacts apart from genuine molecule behaviour.
• Fluency with structured experimental data capture, and proficiency with a LIMS, ELN, or analogous data infrastructure.
• Ready to grow into protocol authorship and SOP ownership over the first twelve months.

NICE TO HAVE

• Direct experience moving biophysical or analytical assays from manual workflows onto lab automation platforms (at least a handoff into an automated platform).
• High throughput experience in at least one core biophysical platform (SPR or BLI for binding kinetics), plus one or more orthogonal characterisation or developability assays (for example nanoDSF/DSF, DLS, analytical SEC, HIC, AC-SINS, cIEF, or CE-SDS).
• Experience developing novel high throughput technologies in DNA generation, cell expression (cell-free, mammalian), or bead-based purification.
• Method development and validation experience: defining acceptance criteria, references, and controls that other scientists have run successfully.
• SOP and protocol authorship that others have executed, and experience supervising at least one junior scientist or technician.
• Experience working with computational or AI/ML colleagues on closed-loop assay programmes.
• Background at an AI-native biotech or foundation-model company.

Why this is unusual

Most protein science roles like this inherit an established workflow and optimise it. This one does not. No assay in this vertical is being retrofitted onto automation; every protocol is designed for AI-in-the-loop execution from the first manual run. The data each assay produces, its output structure, metadata, provenance, and consistency across runs, is treated as a first-class scientific constraint, because that data feeds directly into foundation-model training pipelines. Your decisions at the bench affect what the orchestrator has to do and what data leaves the building.

Some scientists find this energising; others find it outside the lane they trained for. It is worth knowing in advance which one you are.

How we work

This role is on site five days a week at our London Lab. The lab is a physical place and the work is in it.

We work in the open. Decisions are written down, work happens in Slack rather than scattered across tools, and the week is bookended by a Monday kick-off and a Thursday wrap that the whole company attends. There is a quarterly offsite. Each person owns their area and makes the call inside it, and we will expect that of you early rather than late.

UK benefits are 30 days of annual leave plus public holidays, a pension with a 10% employer contribution, and top-tier Bupa private health cover. More is added as the team grows.

The team you will join

You will join the protein sciences vertical, working day to day alongside a senior member of the vertical and the automation engineering and software teams who turn the manual cascade into an automated one.

Our process and how to apply

Our process has four stages. A short screening call about the role and the practicalities. A conversation about how you work, run from the same template for every candidate, before anything technical. A practical exercise drawn from a real problem in our lab, followed by a discussion of what you did and why. Then references, aimed at whatever we still want to understand.

We are an equal opportunity employer. We make hiring decisions on merit, scope-fit, and the strength of the working relationship we expect to build with each hire