Senior AI Engineer- Imaging

F. Hoffmann-La Roche AG; South San Francisco (CA); On-site; USD 168,000 - 312,000; Full time

Job summary

Genentech, a Roche company, is seeking a senior AI/ML software engineer to design, develop, and test scalable CV-based web apps and pipelines for high-throughput imaging data. You will build, evaluate, and fine-tune state-of-the-art models (cell segmentation, classification, and phenotyping) and optimize GPU memory and throughput in cloud environments.

You will collaborate with product managers and researchers to translate complex scientific imaging needs into technical specs, contribute to

Qualifications

• PhD or Master with 3–5 years, or Bachelor with 4–7 years in a technical field focusing on ML and CV.
• Strong proficiency with AI/ML frameworks and CV libraries (PyTorch, TensorFlow, OpenCV, MONAI).
• Deep expertise in CNNs, Vision Transformers, UNet, and quantitative image analysis.
• Experience with high-dimensional imaging data and GPU-accelerated computing.
• Familiarity with cloud-native architectures, Kubernetes, and MLOps basics.

Responsibilities

• Design, develop, and test scalable AI/ML CV applications and pipelines for imaging data.
• Build and fine-tune state-of-the-art CV models for segmentation and classification.
• Evaluate model performance, establish benchmarks, and monitor drift over time.
• Collaborate with product managers and researchers to translate imaging needs into specs.
• Maintain scalable cloud data pipelines and optimize GPU memory and throughput.
• Contribute to architecture, code reviews, and CI/CD/MLOps practices.
• Span full stack work as needed and stay current with CV tech trends.

Skills

Python

Computer Vision

Deep Learning

CUDA

CI/CD

Education

PhD or Master in CS/Engineering

Tools

PyTorch

TensorFlow

OpenCV

MONAI

Scikit-Image

Napari

Bio-Formats

Kubernetes

CUDA

Job description

The Opportunity:

• Design, develop, and test robust, scalable, and maintainable AI/ML scientific web applications and backend pipelines tailored for high-throughput scientific imaging data processing and visualization.
• Build, evaluate, and fine-tune state-of-the-art computer vision and deep learning models (e.g., cell segmentation, cell classification, phenotypic profiling, tissue segmentation, feature extraction, and image registration) applied to biological and clinical imaging modalities.
• Build tools to evaluate AI/ML and vision model performance, establish benchmark datasets, and quantify model quality, robustness, and drift over time.
• Partner with product managers, bioimage analysts, and research scientists to understand user workflows, shape requirements, and translate complex scientific imaging needs into actionable technical specifications.
• Develop and maintain scalable cloud infrastructures and data pipelines for collecting, structuring, storing, and accessing large-scale multi-dimensional imaging datasets (e.g., OME-TIFF, Zarr, HDF5).
• Optimize GPU memory footprint, batching, and inference throughput for large image pipelines and deep neural network models.
• Contribute to architectural decisions, code reviews, and the evolution of engineering and MLOps processes for computer vision models.
• Be willing to span the full stack and contribute where needed, even outside of core areas of expertise.
• Stay up-to-date with emerging computer vision technologies and industry best practices while promoting a culture of continuous learning, collaboration, and curiosity.

Who You Are

• PhD, Master’s with 3–5 years, or Bachelor’s with 4–7 years experience with a degree in Computer Science, Biomedical Engineering, Electrical Engineering, Computational Biology, or a related technical field with focus on machine learning engineering and computer vision.
• Strong proficiency with AI/ML frameworks and computer vision libraries (e.g., PyTorch, TensorFlow, OpenCV, MONAI, Scikit-Image, torchvision, Napari, or Bio-Formats).
• Deep expertise in computer vision algorithms (e.g., CNNs, Vision Transformers, UNet, SAM/Segment Anything, Cellpose).
• Expert knowledge of machine learning theory, image processing fundamentals, object detection, instance segmentation, and quantitative image analysis.
• Demonstrated experience working with high-dimensional scientific imaging data (e.g., fluorescence/brightfield microscopy, digital pathology whole slide images, high-content screening, multiplexed imaging, etc).
• Strong knowledge of GPU acceleration, parallel computing, CUDA, and ML performance optimization for large image datasets.
• Experience with Kubernetes, relational databases, NoSQL databases, object storage, and cloud-native architectures in public clouds (ideally AWS).
• Proven understanding and application of software engineering best practices, CI/CD, and MLOps principles.
• Excellent communication skills and ability to build trusted partnerships with scientific collaborators, bioimage analysts, and cross-functional teams.
• Ability to quickly acquire new technologies, domain knowledge, and programming languages with a passion for continuous learning.

Preferred Qualifications

• Experience with multi-modal data fusion (combining scientific imaging with genomics, transcriptomics, or clinical tabular data).
• Experience working directly with biomedical scientists or in a pharma/biotech research environment.
• Experience with workflow automation, GenAI, Vision-Language Models, and/or AI agents.

Onsite presence on our South San Francisco campus is expected for at least 3 days a week. Relocation Assistance benefits are not available for this posting.

The expected salary range for this position based on the primary location of San Franscico, CA is $168,100- $312,300 Annual.

This position is open to both SE6 and SE7 levels, with final leveling to be determined upon completion of the interview process. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance.

This position also qualifies for the benefits detailed here

Benefits Genentech is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company's policy prohibits unlawful discrimination, including but not limited to, discrimination on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws. If you have a disability and need an accommodation in relation to the online application process, please contact us by completing this form Accommodations for Applicants.

Who We Are

Genentech, a member of the Roche group and founder of the biotechnology industry, is dedicated to pursuing groundbreaking science to discover and develop medicines for people with serious and life-threatening diseases. To solve the world's most complex health challenges, we ask bigger questions that challenge our industry and the boundaries of science to transform society. Our transformational discoveries include the first targeted antibody for cancer and the first medicine for primary progressive multiple sclerosis. The next step is yours.

Genentech is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company's policy prohibits unlawful discrimination, including but not limited to, discrimination on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws. If you have a disability and need an accommodation in relation to the online application process, please contact us by completing this form Accommodations for Applicants.