Scientific Software Engineer

Company: Chemaxon

Location: Location not specified (Remote)

Type: Full-time

Level: mid

Remote: Yes

Posted: 2026-02-19

About this role

About Chemaxon

Chemaxon is an industry-leading cheminformatics software company helping early-stage drug discovery and chemistry research for more than 25 years. Our clients are top pharmaceutical companies, innovative biotech startups, and leading academic institutions. We are agile, innovative and friendly, offering compelling opportunities for frequent collaboration and cross-training with teammates and stakeholders

We have been acquired by Certara, a US-based model-informed drug development services and software company. We are in an exciting time of organizational and business growth, so now is the perfect time to join our team!

About Certara

Certara accelerates the potential of bringing medicines to market and to patients using biosimulation software, technology, and services to transform traditional drug discovery and development. Our clients include more than 2,400 biopharmaceutical companies, academic institutions, and regulatory agencies across 70 countries.

Our goal is to enable the life sciences industry’s use of data, modeling, and analytics to make better decisions across the various phases of discovery and drug development. Our software and scientists incorporate modern advances in scientific understanding, drug development experience, data analysis, and AI resulting in significant opportunities to decrease the cost and increase the probability of success for new drug approval and commercialization.

Certara is seeking a Scientific Software Engineer to join our engineering team and help advance Certara IQ, our quantitative systems pharmacology (QSP) modeling and simulation platform. This role focuses on the core modeling language and simulation engine that power the platform’s pharmacological workflows.

You will work on a small and growing team of seven engineers. You’ll collaborate closely with scientific stakeholders to enhance our modeling language, improve numerical performance, and push the boundaries of pharmacological model simula...

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