Software Engineer

Build software that helps scientists move medicines from discovery to patients.

As one of our early engineers, you'll be driving the development of our AI-enabled toxicology platform, architecting solutions that tackle deeply complex scientific challenges and have real impact in the world. You'll work at the intersection of software engineering and life science, where elegant code meets the messy world of biology.

We are seeking a motivated Software Engineer to join our team developing our AI Toxicology platform for pharmaceutical and other customers. As an early engineer, your decisions will shape our platform, our engineering culture, and how scientists around the world use Sable.

We're looking for people who enjoy:

Building clean, maintainable Python applications that scale to millions of biological data points.

Collaborating with scientists to turn fuzzy scientific questions into production software.

Working on data processing pipelines that ingest, transform, and score large-scale biological and clinical datasets.

Setting the standard for software quality and best practices through thoughtful code reviews, technical discussions, and by leading through example.

Shaping the architecture of our platform to support rapid growth and scientific innovation.

Every feature you build will support scientists in moving drugs from discovery to delivery.

Requirements

Ideal candidates will have:

Strong proficiency in Python, with attention to best practices and testing.

2-3 years of professional software development experience.

Experience in at least one of these areas (we love curiosity in any of them!):

Developer tooling (making life easier for engineers)

AWS or other cloud platforms

Bachelor's degree in Computer Science, Software Engineering, or a related field.

Nice to have:

Background in a biomedical field.

Experience with scientific, bioinformatics, or healthcare data.

Access to quality pirate memorabilia

A note on our approach: You don't need to tick every box. If you're strong in Python, excited by the problem space, and motivated to learn, we'd love to hear from you.

Hybrid working : split your time between home and our office in East London.

Annual training budget : use it to learn new skills, attend conferences, or explore ideas that make you better at your craft.

Private medical plan : access to high-quality healthcare if you need it.

Friday afternoons for personal development : protected time every week to explore, learn, or experiment on what excites you.

Equity in the company : be part of our journey from the ground up.

Shape the future : as an early hire, your work and decisions will influence both our platform and our company culture.

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