Scientific Advisor, Antibodies

About 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 revolutionizing 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  are already used by clients across biopharma, biotech, agri‑tech, food‑tech, and academia.

We’re an experienced team of around 75 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 in the company and a wide range of benefits and career progression opportunities.

As a Scientific Advisor within our Customer Success team, you will play a key role in ensuring our customers achieve success with Cradle’s software and services. You’ll act as a trusted partner of biotech and pharmaceutical companies, particularly for biotherapeutic and antibody projects. As part of this role, you’ll assist customers in mapping their program goals and data to Cradle’s capabilities, using our machine learning platform, and maximising the value and impact of our protein optimisation software.

For this, you’ll collaborate across Cradle’s engineering, product, and sales teams to ensure a superb customer experience and inform product development to build the most sought‑after features.

Work closely with Cradle customers, ranging from medium‑sized biotechs to global biopharma leaders, to:

• Advise on identifying protein optimisation projects within their portfolios that are best suited to the Cradle platform.
• Help translate scientific goals of projects (predominantly biotherapeutics) into objectives for the Cradle platform.
• Deeply understand customer assays/workflows – research modalities/targets as necessary to gain a foundation in relevant concepts, assays and workflows.
• Ensure quality/formatting of customer data is suitable for machine learning.
• Train them to use Cradle’s platform.
• Collaborate with engineering to ensure our platform outputs optimal protein designs to customers.
• Present reports to help the customer interpret and assess platform outputs and forecasts.
• Provide recommendations to inform go/no‑go decisions and devise the most effective strategy for their projects.

• Build and maintain strong relationships with immediate users of Cradle platform within the customer organization, as well as broader business stakeholders. Keep them abreast of results and impact, on both project and portfolio levels.
• Help existing customers identify further projects and business units that would benefit from Cradle’s platform, and collaborate with the Cradle sales team to enable these projects through relationship expansion.

• Measure and monitor satisfaction of the customers with product as well as service.
• Proactively gather customer feedback, and keep the customers informed as their feedback is then turned into improved features and services.
• Collaborate with product teams at Cradle to guide product development so as to address customer needs.

• PhD in molecular biology, bioengineering, bioinformatics, or a related field.
• 5+ years of experience in biopharma in a scientific role in protein engineering, focusing on antibodies, with experience with biophysical and/or functional assays.
• Deep knowledge of the biopharmaceutical R&D process, methods, and tooling.
• Excellent analytical and communication skills, with the ability to translate complex scientific concepts into clear, actionable insights.
• Proven ability to build strong relationships with a variety of stakeholders, including scientists and business leaders.

• Experience with machine learning.
• Exp…