Senior AI Engineer - Biomedical Imaging & CV

Genentech; South San Francisco (CA); On-site; USD 168,000 - 312,000; Full time

Job summary

Genentech is seeking an imaging-focused machine learning engineer to design, develop, and optimize scalable AI/ML and computer vision systems for large-scale biomedical imaging data, including microscopy and digital pathology. You will partner with scientists and product teams to translate workflows into robust software and pipelines in a cloud-enabled environment.

The role demands deep CV expertise (CNNs, ViTs, UNet, SAM) and strong ML theory, with experience in GPU optimization, Kubernetes,

Qualifications

• PhD, Master’s with 3–5 years, or Bachelor’s with 4–7 years in Computer Science, Biomedical Eng, Electrical Eng, Computational Biology, or related field.
• Strong proficiency with AI/ML frameworks and CV libraries (PyTorch, TensorFlow, OpenCV, MONAI, Scikit-Image, torchvision, Napari, Bio-Formats).
• Deep expertise in CNNs, Vision Transformers, UNet, SAM/Segment Anything, Cellpose.
• Expert knowledge of ML theory, image processing, object detection, instance segmentation, and quantitative image analysis.
• Experience with high-dimensional scientific imaging data (fluorescence, digital pathology, high-content imaging).
• Knowledge of GPU acceleration, CUDA, and ML performance optimization for large image datasets.
• Experience with Kubernetes, relational/NoSQL databases, object storage, and cloud-native architectures (AWS).
• Proven understanding of CI/CD and MLOps practices.
• Excellent communication and ability to partner with scientists and cross-functional teams.

Responsibilities

• Design, develop, and test scalable AI/ML scientific web apps and backend pipelines for high-throughput imaging data.
• Build and evaluate state-of-the-art computer vision models for biological/clinical imaging modalities.
• Create tools to benchmark model quality, drift, and robustness over time.
• Translate scientific imaging needs into technical specs with product managers and researchers.
• Develop scalable cloud data pipelines for large multi-dimensional imaging datasets (OME-TIFF, Zarr, HDF5).
• Optimize GPU memory, batching, and inference throughput for large image pipelines.
• Contribute to architectural decisions and CI/CD/MLOps processes for CV models.
• Stay current with CV tech and promote collaboration and continuous learning.

Skills

PyTorch

TensorFlow

OpenCV

MONAI

Scikit-Image

Napari

Bio-Formats

CNNs

Vision Transformers

UNet

SAM/Segment Anything

CUDA

Kubernetes

AWS

CI/CD

MLOps

Communications

Education

PhD/Master’s with 3–5 years or Bachelor’s with 4–7 years in Computer Science, Biomedical Eng, or related field

Relevant imaging or biomedical engineering degree

Tools

Kubernetes

AWS

NoSQL databases

Cloud-native architectures

OOP/CI-CD tooling

Job description

Genentech is seeking an imaging-focused machine learning engineer to design, develop, and optimize scalable AI/ML and computer vision systems for large-scale biomedical imaging data, including microscopy and digital pathology. You will partner with scientists and product teams to translate workflows into robust software and pipelines in a cloud-enabled environment.

The role demands deep CV expertise (CNNs, ViTs, UNet, SAM) and strong ML theory, with experience in GPU optimization, Kubernetes,