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Machine Learning Research Engineer (MLRE) - Workflows/Systems
Summary by AIEngineer.careers
Machine Learning Research Engineer (MLRE) - Workflows/Systems is a Machine Learning Research Engineer role (full-time). with Achira. in SAN FRANCISCO, US. Imported listing (source: feeny.ai). Apply on the employer's site (feeny.ai).
Imported listing (source: feeny.ai) · Apply on feeny.ai
SAN FRANCISCO · US
—
Full-time
MID
The sections below reproduce the third-party job description for reference. AIEngineer.careers does not write or control this text.
Imported job description
Sourced from feeny.ai
Achira is seeking a Machine Learning Research Engineer to bridge the gap between scientific research and distributed infrastructure. The role focuses on architecting scalable workflows for molecular machine learning and foundation simulation models in drug discovery. You will enable scientific teams to conduct large-scale experiments while optimizing ML systems design.
Responsibilities
- Build and maintain robust multi-stage asynchronous workflows for data generation, training, and evaluation.
- Rationalize machine learning systems design and software architecture.
- Identify blockers and build solutions that scale to the size of foundation models.
- Act as the liaison between research scientists and the infrastructure team.
Requirements
- At least two years of relevant industry experience.
- High fluency in PyTorch and JAX.
- Experience with asynchronous programming primitives.
- Strong library design principles: clean abstractions, minimal surface area, consistency.
- Solid track record of well-documented code (e.g., GitHub).
- ML generalist understanding of scalable, reliable ML systems.
Nice to Have
Achira
New York · US · 19+ employees
Achira is developing atomistic world and foundation simulation models for physical AI and drug discovery. Its approach combines machine learning, physics, quantum chemistry, geometric deep learning, generative AI, and statistical mechanics to model how atoms and forces behave.
