Backend Systems Engineer - AI-Driven Lab Automation

Userc Dehradun

Lausanne

Sur place

CHF 120 000 - 180 000

Plein temps

Il y a 2 jours
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Résumé du poste

Adaptyv Lausanne is seeking a Software Engineer, Backend to build backend systems powering an automated biology lab. You will architect data pipelines for large-scale protein characterization data and design APIs to integrate laboratory instruments and robotics with our software stack.

You'll collaborate with scientists and automation engineers to translate complex molecular biology workflows into reliable, scalable software that runs on-site, enabling AI-driven experiments with minimal human

Qualifications

  • Strong experience designing and building production backend systems.
  • Experience building data pipelines and processing infrastructure.
  • Comfortable with API design and systems integration.
  • A genuine interest in biology.
  • High-autonomy, founder mindset.
  • Pragmatism in solving problems.
  • Ability to write code with AI but understand traditional coding.

Responsabilités

  • Build backend systems that make our lab programmable.
  • Architect data pipelines for large-scale protein data processing.
  • Design APIs to integrate laboratory instruments and robotics.
  • Collaborate with scientists and automation engineers to translate workflows into software.
  • Deliver reliable, scalable software for on-site lab operation.

Connaissances

Backend system design
Data pipelines
API design
Biology interest
High autonomy
Pragmatism
AI-assisted coding

Outils

Python
TypeScript
PostgreSQL

Description du poste

Adaptyv Lausanne is seeking a Software Engineer, Backend to build backend systems powering an automated biology lab. You will architect data pipelines for large-scale protein characterization data and design APIs to integrate laboratory instruments and robotics with our software stack.

You'll collaborate with scientists and automation engineers to translate complex molecular biology workflows into reliable, scalable software that runs on-site, enabling AI-driven experiments with minimal human

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