1 day ago
Base Salary
$168k - $312k/yr
Responsibilities
- Design, develop, and test scalable AI/ML scientific web applications and backend pipelines for high-throughput imaging data.
- Build, evaluate, and fine-tune computer vision and deep learning models for biological and clinical imaging.
- Create tools, benchmark datasets, and metrics for assessing model performance, robustness, quality, and drift.
- Develop scalable cloud infrastructure and data pipelines for large multidimensional imaging datasets.
- Optimize GPU memory usage, batching, and inference throughput for image-processing pipelines and neural networks.
- Collaborate with product managers, bioimage analysts, research scientists, and software engineers to translate scientific workflows into technical requirements.
- Contribute to architecture, code reviews, engineering practices, MLOps processes, and continuous learning.
Requirements
- PhD, or a master’s degree with 3–5 years of experience, or a bachelor’s degree with 4–7 years of experience in computer science, biomedical engineering, electrical engineering, computational biology, or a related technical field focused on machine learning engineering and computer vision.
- Strong proficiency with AI/ML frameworks and computer vision libraries such as PyTorch, TensorFlow, OpenCV, MONAI, Scikit-Image, torchvision, Napari, or Bio-Formats.
- Deep expertise in computer vision algorithms including CNNs, Vision Transformers, UNet, SAM/Segment Anything, and Cellpose.
- Expertise in machine learning theory, image processing, object detection, instance segmentation, and quantitative image analysis.
- Experience with scientific imaging data such as microscopy, digital pathology whole-slide images, high-content screening, or multiplexed imaging.
- Knowledge of GPU acceleration, parallel computing, CUDA, and machine learning performance optimization.
- Experience with Kubernetes, relational and NoSQL databases, object storage, and cloud-native architectures, ideally on AWS.
- Understanding and application of software engineering, CI/CD, and MLOps practices.
- Preferred experience includes multimodal data fusion, biomedical or pharma/biotech research collaboration, workflow automation, GenAI, Vision-Language Models, or AI agents.
- Strong communication, collaboration, learning, and cross-functional partnership skills.
Benefits
- Expected onsite presence at the South San Francisco campus at least three days per week.
- Relocation assistance is not available.
- A discretionary annual bonus may be available based on individual and company performance.
- Benefits are provided according to the company’s stated benefits program.
Tech Stack
Categories
About Genentech
Genentech discovers, develops, and commercializes biologic therapies for serious diseases across oncology, immunology, neuroscience, ophthalmology, infectious disease, and metabolism. Founded in 1976 and headquartered in South San Francisco, it operates as a member of the Roche Group, with research centered in its gRED organization and revenue driven by prescription drug sales and collaborations.