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Research Engineer III (ML)
Summary by AIEngineer.careers
Research Engineer III (ML) is a AI Research Engineer role (contract). with Gladstone Institutes. in SAN FRANCISCO, US. Compensation shown: $88K–$120K. Imported listing (source: emploive.com). Apply on the employer's site (emploive.com).
Imported listing (source: emploive.com) · Apply on emploive.com
SAN FRANCISCO · US
$88K–$120K
Contract
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 emploive.com
Gladstone Institutes is seeking a mid-level ML Research Engineer to join the Finkbeiner Lab in San Francisco. This role focuses on applying computer vision and reinforcement learning to biomedical imaging data, specifically for neurodegeneration research and automated microscopy systems. The engineer will collaborate with biologists to deploy scalable AI pipelines and fine-tune multimodal models.
Responsibilities
- Design and deploy computer vision and reinforcement learning pipelines for high-content cellular imaging.
- Train, fine-tune, and benchmark multimodal models for pathology and cell segmentation.
- Collaborate with interdisciplinary teams to streamline AI/ML workflows and resolve computational bottlenecks.
- Contribute to grant writing and scientific manuscripts by developing computational aims and methods.
Requirements
- Bachelor's degree in engineering, CS, physics, or related field with 4+ years of experience (or MS with 2+ years).
- Hands-on experience with deep learning frameworks like PyTorch, JAX, OpenCV, and Hugging Face.
- Proficiency with MLOps tools including Docker, Kubernetes, and Slurm.
- Strong background in machine learning, computer vision, transformer architectures, and reinforcement learning.
Gladstone Institutes
San Francisco · US · 600+ employees
Gladstone Institutes is an independent, nonprofit biomedical research organization dedicated to overcoming disease. It focuses on disease-oriented science, particularly in the fields of cardiovascular disease, immunology, virology, neuroscience, and data science.
