ML Research Engineer - GPUs go Brrr

Join a world-class team of scientists, ML researchers, and engineers working together to make the physical microcosm predictable and reshape the future of drug discovery. We're looking for a rare individual who thrives at the intersection of cutting-edge deep learning architectures and high-performance computing.

Requirements

• Implement state-of-the-art Graph Transformers, GNNs, and similar geometric deep learning architectures into production-ready pipelines.
• Drive end-to-end performance — from high-level implementations in PyTorch / JAX down to hand-tuned CUDA kernels — to extract maximum throughput, minimize memory footprints, and optimize GPU compute bubbles.
• Help scale training and inference workloads across thousands (and eventually tens of thousands) of GPUs, maximizing FLOPs, saturating caches, and pushing hardware to its limits.
• Collaborate closely with scientists and ML researchers to identify, evaluate, and develop novel architectures with superior inductive biases for molecular modeling.
• Simulate molecular systems with unprecedented speed and accuracy — enabling breakthroughs in drug design, protein modeling, and beyond.
• Utilize generative coding tools to accelerate work and ultimately automate optimization workflows.

Benefits

• Competitive salary and benefits package
• Opportunity to work on cutting-edge projects and technologies
• Collaborative and dynamic work environment