Ai Bio
Protein Production Scientist, Biologics
Salary not disclosed2+ yearsOnsite
- Protein Sciences
- London
- Full time
- Today
About the role
You will build a protein production cascade that turns sequences into quality-controlled protein at scale, moving from manual protocols to an automated platform. This role involves DNA design, molecular biology, protein expression, purification, and quality control, with a focus on data traceability and reproducibility. You will work at the intersection of bench science, automation engineering, and software development to create infrastructure for AI-driven biological research.
Responsibilities
- Develop and run manual protein production workflows including DNA design, expression, and purification
- Establish reproducibility, precision, and quality thresholds for assay protocols
- Collaborate with automation and software teams to transition manual assays to an automated platform
- Author SOPs and document experimental protocols for the assay portfolio
- Perform high-throughput protein characterization and data analysis
- Contribute to the design of the protein production cascade and assist in interviewing new team members
Required skills
- Protein biochemistry
- Molecular biology
- Protein expression
- Protein purification
- High throughput screening
- DNA design
- Biologics
- Data analysis
- LIMS
- ELN
Nice to have
- Lab automation
- Binding kinetics
- SPR
- BLI
- Method development
- Protocol authorship
- AI/ML collaboration
Qualifications
- PhD in protein biochemistry, molecular or structural biology, biophysics, analytical characterisation, or biologics developability with 2+ years of relevant experience
- MSc in a relevant science with 5+ years of equivalent bench experience in protein science
Benefits
- 30 days annual leave
- Public holidays
- Pension with 10% employer contribution
- Bupa private health cover
About the Company
Ai Bio is an AI-native company building infrastructure to produce high-quality, traceable biological data. The company is currently in stealth mode and focused on developing automated protein production cascades.