Genesis Molecular AI

About the Company

Genesis Molecular AI – headquartered in Burlingame, CA, with a fully integrated laboratory in San Diego and offices in New York – is pioneering foundation models for molecular AI to unlock a new era of drug design and development. We are using a proprietary state-of-the-art generative and predictive AI platform called GEMS (Genesis Exploration of Molecular Space), to accelerate and optimize small molecule drug discovery. The GEMS platform integrates AI and physics into industry-leading models to generate and optimize drug molecules, including the breakthrough generative diffusion model Pearl for structure prediction. GEMS accelerates hit ID through lead optimization and candidate selection by generating promising molecules for synthesis and experimental testing, and iterating this process through cycles of AI-enabled discovery and optimization. We have leveraged GEMS to build an internal pipeline with multiple programs against high-value targets, including data-poor and canonically undruggable targets where GEMS is uniquely advantaged. In addition, Genesis has signed AI platform collaborations across a range of therapeutic areas including Gilead (2024), and Incyte (2025). Genesis has raised over $300M in funding from top AI, technology and biotech investors, including Andreessen Horowitz, Rock Springs Capital, T. Rowe Price, Fidelity, Radical Ventures, NVentures (NVIDIA's VC arm), BlackRock, and Menlo Ventures. To learn more about Genesis Molecular AI, or current employment opportunities, please visit our website.

Listed Jobs

Company Name

Genesis Molecular AI

Job Title

Software Engineer Intern - 2026

Job Description

Job Title: Software Engineer Intern – 2026 Role Summary: Design, develop, and scale software tools for molecular visualization, model analysis, and chemical workflow management within a drug discovery platform. Collaborate with machine‑learning engineers and medicinal chemists to productionize algorithms for molecular property prediction and to handle large‑scale data and compute workloads. Expectations: Deliver high‑quality, maintainable code rapidly; apply first‑principles reasoning rather than pattern matching; demonstrate eagerness to learn biochemistry and drug‑development science; work effectively in cross‑disciplinary teams and contribute to continuous improvement of infrastructure and software quality. Key Responsibilities: • Build and extend web‑based and command‑line utilities for visualizing molecules and proteins. • Integrate and evaluate machine‑learning models for predicting chemical properties. • Automate and streamline complex chemical workflows, ensuring reliability and reproducibility. • Scale core infrastructure (data storage, compute clusters, and job schedulers) to support billions of data points and thousands of concurrent deep‑learning/molecular‑dynamics jobs. • Collaborate with ML engineers and medicinal chemists to prototype, test, and deploy new computational methods into production. • Maintain and improve code‑base quality (unit testing, code reviews, documentation, CI/CD). • Monitor system performance and troubleshoot production issues. Required Skills: • Proficiency in software development (Python, C++, or analogous languages). • Experience with deep‑learning frameworks (TensorFlow, PyTorch) and parallel computation. • Familiarity with molecular dynamics software and computational chemistry workflows (e.g., GROMACS, AMBER). • Strong understanding of data pipelines, database design, and cloud infrastructure (AWS/GCP/Azure). • Knowledge of version control (Git), CI/CD, automated testing, and debugging practices. • Ability to reason from first principles, solve complex problems, and convey technical concepts to multidisciplinary stakeholders. Required Education & Certifications: • Current undergraduate or graduate student in Computer Science, Software Engineering, Computational Biology/Chemistry, or a related field. • Completed coursework or projects in machine learning, data science, or computational chemistry is advantageous. • No specific certifications required; a commitment to continuous learning in AI/ML and life‑sciences disciplines is essential.

Burlingame, United states

On site

Fresher

29-10-2025