Research Engineer

Machine Learning Research Engineer – Research
Ready to operate at the cutting edge of applied AI research and molecular simulation? This role is perfect for individuals who excel at both scientific rigor and engineering excellence, building architectures and prototypes that push the boundaries of molecular modeling.

The Employer
Join an organization creating the next generation of AI-driven drug discovery platforms, integrating advanced machine learning with biological and chemical sciences. With world-class peers, abundant resources, and a mission-driven culture, this is where ambitious engineers shape the future.

Qualifications & Experience
Strong foundation in software engineering for ML research.
Hands-on experience with PyTorch, JAX, and HPC environments.
Able to design scalable research pipelines and write production-ready code.
Deep scientific engagement through a PhD or equivalent experience.

Responsibilities
In this role, you will:
Run and analyze experiments to advance next-gen foundation models.
Architect reproducible pipelines for training and evaluation.
Implement cutting-edge architectures from literature and internal research.
Prepare manuscripts, open datasets, and software libraries for release.

Skills / Technical Competencies
Large-scale distributed training systems.
Reproducible research methodology and code quality.
Understanding of modern ML stacks and evaluation metrics.

Nice to Haves
Expertise in equivariant models, geometric deep learning, GNNs, or diffusion models.
Contributions to open-source scientific or ML projects.

This hybrid role is based in San Francisco (preferred) or New York, with regular travel for collaboration and events.
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