Machine Learning Research Engineer (MLRE) - Workflows/Systems
Achira · San Francisco Office
About this role
**Machine Learning Research Engineer (MLRE) - Workflows/Systems** **About Achira** Building world-class teams of scientists, ML researchers, and engineers to advance drug discovery through AI × Chemistry. Developing world models for the physical microcosm to make molecular-level biology learnable, predictable, and designable. **The Role** Architect the future of molecular machine learning by enabling scientific teams to conduct experiments at scale. You'll work at the intersection of ML systems architecture and distributed computing, pushing foundation simulation models forward. **Location** San Francisco (preferred) or New York City (with SF travel as needed). Hybrid roles with office collaboration required. Travel to conferences and corporate events included. **What You'll Do** • Build and maintain robust multi-stage asynchronous workflows for data generation, training, and evaluations • Rationalize ML systems design and software architecture • Identify blockers and build scalable solutions for foundation models • Bridge research scientists and infrastructure teams **Requirements** • 2+ years relevant industry experience • Expert-level proficiency in PyTorch and JAX • Strong asynchronous programming mindset • Strong library design principles: clean abstractions, minimal surface area, consistency • Observable track record of clear, well-documented code (e.g., GitHub) • ML generalist understanding of scalable, reliable systems **Nice to Have** • Experience with equivariant architectures, geometric deep learning, or GNNs (NequIP, MACE, SchNet, PaiNN) • ML-assisted drug discovery background • Declarative workflow orchestration (Flyte, Dagster, etc.) • Comfort collaborating with quantum chemical scientists
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