Senior AI Imaging Engineer: Vision for Life Sciences

Genentech, Inc.; South San Francisco (CA); Sur place; USD 168 000 - 312 000; Plein temps

Avantages offerts par ce poste

Onsite campus in South San Francisco

Discretionary annual bonus eligibility

Résumé du poste

Genentech, Inc. is seeking an imaging-focused machine learning engineer to design, build, and scale AI/ML workflows for high-throughput scientific imaging data such as microscopy and digital pathology.

You will enable richer phenotypic analysis and faster discoveries by bridging scientific intuition with quantitative analysis. You will collaborate with scientists, bioimage analysts, and software engineers to deploy robust computer vision models, optimize GPU usage, and maintain cloud-native

Qualifications

• PhD, MSc or BSc in a technical field with ML/vision focus.
• Strong proficiency with PyTorch, TensorFlow, OpenCV or MONAI.
• Experience applying CV/ML to biological imaging data.

Responsabilités

• Design, develop, and test scalable AI/ML web applications and pipelines for high-throughput imaging.
• Build and fine-tune state-of-the-art computer vision models for biology/clinical imaging.
• Develop benchmarks, evaluate model quality, and monitor drift over time.
• Collaborate with scientists to translate imaging needs into specs.
• Maintain cloud infrastructures and data pipelines for large datasets.

Connaissances

ML engineering

Computer vision

Python

Communication

Formation

PhD/MSc/BSc in CS/BME/EE/Computational Biology

Outils

PyTorch

TensorFlow

OpenCV

MONAI

Napari

Bio-Formats

Description du poste

Genentech, Inc. is seeking an imaging-focused machine learning engineer to design, build, and scale AI/ML workflows for high-throughput scientific imaging data such as microscopy and digital pathology.

You will enable richer phenotypic analysis and faster discoveries by bridging scientific intuition with quantitative analysis. You will collaborate with scientists, bioimage analysts, and software engineers to deploy robust computer vision models, optimize GPU usage, and maintain cloud-native