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Solutions Consultant, Machine LearningCRADLE OF FORESTRY IN AMERICA INTERPRETIVE ASSOCIATION, THE • United States
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Solutions Consultant, Machine Learning

CRADLE OF FORESTRY IN AMERICA INTERPRETIVE ASSOCIATION, THE
  • US
    United States
  • US
    United States
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À propos

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 at scale. We are already used by clients across biopharma, biotech, agri-tech, food-tech, and academia. We're an experienced team of around 90 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. The Role
As a ML-focussed Solutions Consultant on our Commercial team, you're the person who speaks fluently with the computational teams at biotech and pharma companies that are building serious in-house ML capabilities. You'll partner with Account Executives across the full buying journey, owning the technical narrative with ML engineers, computational biologists, and research leaders who want to understand not just what Cradle does, but how it works and why it's better than other platforms. You'll bring genuine ML depth to every conversation, and feed what you learn back to the teams building the product. Your Impact
Own the technical discovery process with prospects — understanding their computational stack, ML workflows, and protein engineering objectives to position Cradle where it creates the most value
Build and deliver compelling technical demonstrations that speak directly to ML-savvy audiences, including engineering and research leadership
Drive the conversation with computational and ML teams at prospects, handling deep technical questions with authority and earning credibility fast
Shape how Cradle tells its ML story externally — developing presentations, demos, and assets that set a new bar for technical sales at the company
Feed insights from the field into the product and ML teams, influencing roadmap decisions with ground-truth intelligence from the market
Partner with and mentor other SSCs, helping the team grow its technical depth over time
Your Expertise
Great candidates will have experience with most of the following areas, while being eager to develop in others: A graduate degree (MS or PhD) in machine learning, computational biology, computer science, or a closely related field
Hands-on ML engineering experience — you've trained models, worked with sequence or structure data, and understand the stack from data pipeline to deployment
Familiarity with protein engineering or structural biology contexts — you don't need to have run a wet lab, but you understand the problems these scientists are trying to solve
Ability to translate technical depth into clear, persuasive narratives for mixed audiences — from ML engineers to executives
Comfort working in a fast-moving, customer-facing role where no two conversations are the same
Willingness to travel 20–30%, including internationally
Nice to Haves Prior experience in a solutions consultant, sales engineering, or customer-facing technical role
Exposure to large language models for biological sequences, diffusion models for structure, or related techniques
Experience with scientific software ecosystems (LIMS, ELN, computational toolchains used in biopharma R&D)
A track record of building technical assets — demos, benchmarks, write-ups — that help others understand complex systems
Our Commitment to Inclusive Hiring Cradle evaluates all candidates based on merit, regardless of sex, gender, ethnicity, socio-economic background, or any other aspect of identity. We maintain zero tolerance for discrimination and actively encourage candidates from all backgrounds to apply. AI Disclosure Cradle uses an applicant tracking system that includes basic AI-assisted features which may generate scores or rankings based on how applications match a job description. These outputs are not used to make or meaningfully influence hiring decisions — all candidates are evaluated through a thorough, human-led review by our recruiting team. 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.
  • United States

Compétences linguistiques

  • English
Avis aux utilisateurs

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