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ML Research Scientist (MLRS) - Generative AI

Achira · San Francisco Office

hybridunknown$164,638–$259,000Posted Jun 30, 2026PythonPyTorchJAXdiffusion modelsautoregressive modelsflow-based modelsreinforcement learningprobabilistic inference

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About this role

## WHY ACHIRA At Achira, we’re building a team of world-class scientists, ML researchers, and engineers to push beyond the beaten path and create a frontier lab for **Physical AI for molecules**. We’re exploring the next frontier of **model architectures for AI × Chemistry**—developing **world models for the physical microcosm**. Our goal is to make **biology at the molecular level** something that 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** to **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 looking for **Machine Learning Researchers** to shape the frontier of **generative models** for the **atomistic microcosm**. You’ll work at the intersection of **cutting-edge machine learning**, **statistical mechanics**, and **approximate Bayesian inference** to tackle **sampling and generation** challenges at light-speed. You’ll also collaborate with experts in **chemistry and physics** to invent and implement models and applications that unlock what’s possible for Achira’s microscopic world models. **Location / Travel:** - Prefer working from **San Francisco** (highly skilled candidates may be considered for **New York City** with travel to San Francisco as needed) - Both locations are **hybrid** (spend at least some time in the office) - **Travel** is part of all roles (conferences + corporate on-site activities) --- ## WHAT YOU’LL DO - Invent advanced **sampling and simulation methods** integrating **probabilistic inference**, **deep learning**, and **reinforcement learning** to enable efficient exploration and simulation of learned energy landscapes for molecular systems. - Design and train frontier **generative models**: **diffusion**, **autoregressive**, **flow-based**, and **latent-variable** architectures. - Build models that map between **data distributions** to bridge the gap between **simulation and reality**. - Prototype, benchmark, and iterate rapidly to turn research ideas into reusable, scalable components across Achira’s ecosystem. - Collaborate with **physicists and chemists** to ensure models are grounded in real physics. - Work with **research engineers** and the **infrastructure team** to identify where research ideas need support to deliver effective results. --- ## ABOUT YOU - Interested in building generative models that describe **real matter**. - Drive to build at the frontier of what’s possible and try **high-risk ideas**. - ML researcher with professional experience (post-degree) in an **industry setting**. - Demonstrated research impact via **conference talks/publications** (ML venues), **open-source contributions**, or **released models**. - Strong interdisciplinary communication and presentation skills; able to translate ideas to colleagues from non-ML backgrounds. - Proficiency in **Python** and modern ML frameworks (**PyTorch, JAX**). - Experience collaborating on research projects across **multi-person teams**. - Desire and comfort working on frontier problems in **physical AI** to define how they’ll be tackled. --- ## NICE TO HAVE Achira values excellent ML researchers from many backgrounds—apply even if you don’t have all of these. - Experience with models operating on **3-D po

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