This is Cradle

Proteins are the molecular machines of life, used for many therapeutic, diagnostic, chemical, agricultural and food applications. Designing and optimizing proteins takes a lot of expert knowledge and manual effort, through the use of custom computational and biological tools.

Machine learning is revolutionising this space, by enabling high-fidelity protein models. At Cradle, we offer a software platform for AI-guided discovery and optimization of proteins, so that biologists can design proteins faster and at scale. We are already used by clients across pharma, biotech, agritech, foodtech, and academia.

We're an experienced team of roughly 60 people. We've built many successful products before and have enough funding for multiple years of runway. We are distributed across two main locations, Zurich and Amsterdam, and are focused on building the best possible team culture.

We offer our employees a very competitive salary, a generous equity stake (for full time employees) in the company and a wide range of benefits and career progression opportunities.

Your Role

We're seeking a Head of Large Libraries to build massive scale experimental capabilities to generate large datasets. You'll lead and grow laboratory capabilities that produce more than 10^6 data points for antibody optimization (primary focus), enzyme engineering, and other protein classes. These datasets will power the Cradle platform to strengthen design recommendations, accelerate protein optimization, and deepen our understanding of protein optimization across applications. This is a rare opportunity to build world class screening capabilities that will further advance our ML models and further improve how our users do protein engineering.

Your Responsibilities

Technical Leadership & Innovation

• Build large-scale library capabilities incorporating technologies like FACS, yeast display, mRNA display, microfluidics, and other high-throughput screening platforms to generate datasets with >10^6 data points

• Develop novel assays and experimental strategies for antibody optimization, enzyme engineering, and emerging protein modalities with statistical rigor for ML applications

• Establish end-to-end workflows from DNA synthesis through screening to NGS analysis, owning data standardization and ML pipeline integration

Team Leadership & Collaboration

• Build and lead a world-class team of researchers, scaling the organization to meet ambitious growth targets

• Mentor team members and collaborate across disciplines with ML, software engineering, and platform teams

Strategic Development

• Set long-term strategy and roadmap for scaling library capabilities while staying at the forefront of competitive developments and emerging technologies

• Develop strategic partnerships with CROs, academic collaborators, and technology vendors, and engage with customers to shape experimental priorities and market alignment

Operations & Infrastructure

• Lead laboratory infrastructure planning and process optimization, including equipment procurement, automation setup, and workflow standardization for maximum throughput

• Manage budgets, resources, and documentation systems to ensure operational excellence and knowledge transfer across the organization

Your Qualifications

Required Qualifications

• PhD in relevant field (biochemistry, molecular biology, protein engineering, or related)

• Significant industry experience with a proven track record in large-scale protein library generation and screening

• Demonstrated expertise in managing >10^6 variant libraries and high-throughput screening technologies

• Deep technical knowledge spanning DNA synthesis, library construction, multiple display platforms, FACS, and NGS analysis

• Proven leadership experience building and managing technical teams in fast-paced environments

Technical Expertise

• Hands-on experience with large protein libraries (yeast display, phage display, mRNA display, or similar platforms)

• Proficiency in FACS and other high-throughput screening methodologies

• Understanding of statistical experimental design and data quality requirements for ML applications

• Experience with automation and scaling laboratory processes

• Knowledge of antibody engineering and optimization workflows

Leadership Qualities

• Exceptional communication skills for cross-functional collaboration

• Building mindset with ability to establish new capabilities quickly and efficiently

• Growth mentality with demonstrated ability to learn new areas rapidly and teach others

• Ownership orientation with track record of delivering results in ambiguous environments

A notice about recruitment scams: Please be aware that scammers are posing as us in order to get your personal details or money. We only communicate via @cradle.bio email addresses, we only make job offers after having met you in person at our office in Zurich or Amsterdam, and we never ask you to pay for anything during the interview process.