Fermentation Scientist

Job Description

Biology is the most powerful technology on the planet. It can feed the world, replace petrochemicals, and grow materials we currently mine or refine. The problem is that turning a promising organism into a working production process still takes 5+ years and millions of dollars, and half the time it fails anyway, not because the biology was wrong, but because making biology viable as a product at commercial scale with current tools is a monumental task.

Biology is the most powerful technology on the planet. It can feed the world, replace petrochemicals, and grow materials we currently mine or refine. The problem is that turning a promising organism into a working production process still takes 5+ years and millions of dollars, and half the time it fails anyway, not because the biology was wrong, but because making biology viable as a product at commercial scale with current tools is a monumental task.

Reshape builds the operating system for biotech R&D: hardware, software and data science products that capture, structure and analyze data to enable R&D and QC workflows to be much more effective. Hyperscale is our newest and most ambitious bet inside that mission - a full biological engineering suite that takes a product from 96-well plate to full production scale 10x faster and cheaper compared to traditional bioprocess development.

We're building this from the ground up, in-house, in our Copenhagen lab: our own bioreactor fleet across scales, our own data capture layer, and partnering with impressive companies for real strains and processes to prove the whole thing works.

Job requirements

You'll be the person with the deepest hands-on knowledge on the ins and out of fermentation and process development. You’ll be a key subject matter expert in the team and contributor, both in the science and engineering of bioprocess and scale-up, but also hands-on in actually designing studies, running data in the lab across a set of bioreactors or working with partners to characterize strains, vessels and processes.

This isn't a role where someone hands you a fixed SOP. You're one of the first scientists on a program with no existing playbook, process or platform, working directly with our team across science, hardware, software and data science to decide what to run and why, how to run it, and what to measure. You'll coordinate fermentation runs end to end, own primary data collection and analysis, and build foundational datasets - across organisms, media, and scales - that our predictive models and our pitch to strategic partners both depend on.

At a glance

• Run the fermentations: Coordinate and execute runs across scales — from 96-well through bioreactors ranging from 40ml to 15 liters internally to study key phenomena in media optimization and process engineering
• Own the data: Primary data collection and analysis on every run — titer, yield, productivity, and the critical process parameters (temperature, agitation, pH, DO, kLa, shear) that build the foundation of our understanding
• Drive the science: Use your combination of subject matter expertise in fermentation and first principles thinking to drive scientific reasoning and study designs
• Cross-functional core: Partner daily with the broader science team and our hardware/software teams to close the loop between strain, process, and data capture.
• Partnerships: Help contribute to partnership projects and work with large-scale fermentor data and vessel characterization

Job responsibilities

Someone who has truly felt the gap between benchtop and pilot manufacturing firsthand and who has well formed opinions about why processes break when they scale. You're a fermentation generalist across the funnel rather than a narrow specialist in one unit operation. Ideally, you’ve been part of upscaling several different strains and processes successfully in previous roles.

You're comfortable with ambiguity and building tools as you go. You default to data and root-cause reasoning/first principles thinking over "that's how it's always been done.". You want ownership and urgency and to help build something amazing with a super talented group of people, attacking bioengineering and building tools with a fresh set of eyes.

What success could look like

• First two months: Understand the reactor and data stack, reproduce key baseline processes, and establish a consistent run, sampling, and data-review workflow.
• Within four months: Deliver repeatable datasets across multiple organisms or process conditions and identify the most important scale-dependent failure modes.
• Within nine months: Demonstrate a scale-down or transfer methodology against pilot or production data and materially influence the Hyperscale product roadmap.

What you bring

• Hands-on experience run