3 days ago
Base Salary
$168k - $312k/yr
Responsibilities
- Design, develop, test, and maintain 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 segmentation, classification, phenotypic profiling, feature extraction, and image registration.
- Create model evaluation tools and benchmark datasets to measure quality, robustness, and drift over time.
- Develop cloud infrastructure and data pipelines for large-scale multidimensional imaging datasets.
- Optimize GPU memory usage, batching, and inference throughput for image-processing pipelines and neural networks.
- Partner with product managers, bioimage analysts, research scientists, and scientific collaborators to translate workflows into technical requirements.
- Contribute to architecture, code reviews, engineering processes, and MLOps practices for computer vision models.
- Contribute across the full stack and stay current with emerging computer vision technologies.
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.
- 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.
- Expert knowledge of 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.
- Strong knowledge of GPU acceleration, parallel computing, CUDA, and ML performance optimization.
- Experience with Kubernetes, relational and NoSQL databases, object storage, and cloud-native architectures, ideally on AWS.
- Understanding and application of software engineering best practices, CI/CD, and MLOps principles.
- Strong communication skills and ability to collaborate with scientific and cross-functional teams.
- Preferred qualifications include multimodal data fusion, biomedical or pharma/biotech research experience, workflow automation, GenAI, vision-language models, or AI agents.
Benefits
- The role is expected to be onsite at the South San Francisco campus at least three days per week.
- Relocation assistance is not available for this posting.
- The position qualifies for Genentech benefits, and a discretionary annual bonus may be available based on individual and company performance.
Tech Stack
Categories
About Roche
Roche is a Swiss healthcare company that develops and sells prescription pharmaceuticals and in vitro diagnostic systems for hospitals, laboratories, and clinicians. Its business spans two core divisions—Pharmaceuticals and Diagnostics—with strengths in oncology, immunology, neuroscience, infectious diseases, and diabetes care. Founded in 1896 and headquartered in Basel, Switzerland, Roche also advances personalized healthcare by pairing therapies with companion diagnostics.