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As a Cloud Platform Engineer, you will design and manage cloud infrastructure while collaborating with diverse teams to enhance software development practices and contribute to technical decisions.

Isomorphic Labs seeks to recruit interested candidates for roles in software engineering, machine learning research, computational chemistry, and project management for future openings.

As a Software Engineer, you will design and manage cloud infrastructure, enhance DevOps practices, and collaborate with teams to drive innovation in drug discovery.

The Principal Software Engineer will ensure the reliability and scalability of AI systems, leading infrastructure improvements and optimizing ML workflows.

Design and develop novel machine learning models and training algorithms for drug discovery. Lead and run research projects, implement and scale training/inference frameworks, analyze experiments, and collaborate across disciplines. Mentor and provide technical guidance to other ML researchers and contribute to research direction and presentations.

Manage complex IND submission processes, ensuring integration of non-clinical and clinical aspects, while coordinating teams and refining workflows for pre-clinical development.

Lead DMPK strategy for drug discovery projects, design data-driven ADME/PK experiments and screening cascades, integrate DMPK/PD/tox data for decision-making, define quantitative pharmacology approaches, author regulatory DMPK sections, and collaborate with chemistry, preclinical, clinical, and ML teams to optimize molecule design and predictive models.

Lead the development of quantitative pharmacology strategies for drug discovery projects, leveraging AI models for biologics and small molecules, while mentoring junior team members.

As a Research Scientist focused on Large Language Models, you'll develop and apply advanced ML techniques in drug discovery, contributing to groundbreaking research and leading projects in a collaborative environment.

As a Software Engineer, you'll design and manage GPU/TPU infrastructure targeting AI/ML workloads, collaborating across teams to optimize performance and ensure reliability of machine learning systems.