Machine Learning Research Engineer (MLRE) - GPUs
Achira · San Francisco Office
About this role
## Why Achira At Achira, we’re building a team of world-class scientists, ML researchers, and engineers to move beyond the beaten path in drug discovery. We’re exploring the next frontier of **AI x Chemistry**—developing **world models for the physical microcosm**—so biology at the molecular level can be **learned, predicted, and designed**. You’ll operate at the frontier scale of **massive compute, massive data, and massive ambition**, owning impactful work end-to-end—from **ideation** and **architecture** to **deployment** on distributed infrastructure. We value **rigor, speed, execution, and ownership**, and we’re looking for collaborators who share a sense of relentless urgency. ## About the Role We’re seeking a rare individual who thrives at the intersection of **cutting-edge deep learning architectures** and **high-performance computing**. You’ll help shape molecular machine learning by engineering **high-efficiency implementations** of advanced architectures for **foundation simulation models**, accelerating simulations to the limits of the hardware while maintaining **fidelity to the underlying physics**. **Location / Travel:** We prefer candidates willing to relocate to **San Francisco** or **New York City**, but we can consider **full-time remote** candidates of exceptional talent who are willing to **travel frequently** to our two office sites. Travel is part of all roles, including conferences and corporate on-site activities. ## What You’ll Do - Take existing **PyTorch** and **JAX**, **profile and optimize** without compromising **model accuracy, reproducibility, and robustness** with respect to scientific objectives. - Develop with frameworks like **CUDA, Triton, Warp**, etc. to accelerate **performance-critical** code sections. - Liaise with **NVIDIA** to represent our needs and implement their tooling in our environment. - Work day-to-day with scientists to identify areas of greatest impact, including travel to our **SF and NY working groups**. ## About You - **At least 2 years** of professional experience in **GPU optimization**. - Deep understanding of **GPU programming fundamentals**. - A solid track record of observable artifacts (e.g., **GitHub**) showing optimization work. - Experience collaborating on software projects across **multi-person teams**. ## Nice to Have Even if you don’t have these, we encourage you to apply: - Experience working with **multi-cloud distributed compute** systems. - Experience working with **multi-site distributed** company teams. - Experience with **equivariant architectures** operating on **3-D point clouds**.
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