Senior ML Research Engineer - Biomedical Imaging

Gladstone Institutes; San Francisco (CA); On-site; USD 88,000 - 120,000; Full time

Benefits offered by this job

Competitive salary

Comprehensive benefits

Healthy work-life balance

Growth opportunities

Free shuttle

Job summary

Gladstone Institutes in San Francisco is seeking a ML Research Engineer to apply AI/ML to biomedical imaging and neurodegeneration projects. You will collaborate with biologists, imaging scientists, and engineers to accelerate experiments and develop tools for data-driven discovery.

You will translate complex ML concepts for interdisciplinary collaborators, contribute to manuscripts and grant proposals, and help scale cell image analysis pipelines and the live-cell “thinking microscope” platform.

Qualifications

• Requires Bachelor's degree in engineering, CS, physics or related field.
• 4+ years of related experience for BS/BA or 2+ years for MS.
• Experience in ML, DL, CV, transformers and reinforcement learning.
• Familiar with PyTorch, JAX, OpenCV, Hugging Face, Docker, Kubernetes.

Responsibilities

• Deploy CV and RL pipelines for high-content cellular imaging data.
• Train, fine-tune multimodal models for pathology and cell segmentation.
• Streamline AI/ML workflows and resolve bottlenecks in experiments.
• Contribute to manuscripts and grant proposals.
• Translate complex ML concepts for interdisciplinary teams.

Skills

Deep learning

Computer vision

Reinforcement learning

Transformer architectures

Communication

Education

Bachelor’s degree in engineering, computer science, physics or related field

Master’s degree in a related field

Tools

PyTorch

JAX

OpenCV

Hugging Face

Docker

Kubernetes

Slurm

Job description

Gladstone Institutes in San Francisco is seeking a ML Research Engineer to apply AI/ML to biomedical imaging and neurodegeneration projects. You will collaborate with biologists, imaging scientists, and engineers to accelerate experiments and develop tools for data-driven discovery.

You will translate complex ML concepts for interdisciplinary collaborators, contribute to manuscripts and grant proposals, and help scale cell image analysis pipelines and the live-cell “thinking microscope” platform.