Achira
Machine Learning Research Engineer (MLRE) - Workflows/Systems
San Francisco Office
Sponsorship not specifiedDetected 84 days ago
GitMachine LearningDeep LearningPyTorchAI OrchestrationResearchCollaboration
About the role
- We're looking for a rare individual who thrives at the intersection of machine learning systems architecture and distributed computing.
- You will help architect the future of molecular machine learning by enabling our scientific teams to flexibly conduct experiments at scale, pushing the boundaries of foundation simulation models.
- While we prefer candidates willing to work from our San Francisco office, highly skilled candidates may be considered for working from New York City with travel to San Francisco as needed.
Responsibilities
- Identify blockers and build solutions that scale to the size of foundation models.
- Strong views on library design: clean abstractions, minimal surface area, consistency.
- 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 own impactful work end-to-end, from ideation to architecture to deployment on distributed infrastructure.
Nice to have
- Lack of fear around interacting with quantum chemical scientists and their data pipelines.
Benefits
- Build and maintain robust multi-stage asynchronous workflows for running data generation, training, and evaluations for our machine learning stack.
- Rationalize machine learning systems design and software architecture.
Company info
- At Achira, we are building a team of world-class scientists, ML researchers, and engineers to work together to move beyond the beaten path in drug discovery.
- We are actively exploring the next frontier of model architectures for
- We are a well-funded, talent-dense organization that values rigor, speed, execution, and an ownership mindset.
- We're looking for new members who share our sense of relentless urgency and are natural collaborators who value team success.
This listing is sourced directly from Achira's careers page and normalized into a canonical job model.