Senior AI Engineer (Imaging)

Location: South San Francisco, California, United States of America; hybrid schedule with onsite presence expected at least 3 days per week. Relocation assistance is not available.

Salary: $168,100–$312,300 annual, based on the primary San Francisco, California location. A discretionary annual bonus may be available.

Company

hirify.global is a biotechnology company advancing scientific research and developing treatments for serious and life-threatening diseases.

What you will do

• Design, develop, test, and maintain scalable AI/ML scientific web applications and backend pipelines for high-throughput scientific imaging data.
• Build, evaluate, and fine-tune computer vision and deep learning models for cell segmentation, classification, phenotypic profiling, tissue segmentation, feature extraction, and image registration.
• Create benchmark datasets and tools for measuring model quality, robustness, performance, and drift.
• Partner with product managers, bioimage analysts, research scientists, and cross-functional collaborators to translate scientific imaging workflows into technical specifications.
• Develop cloud infrastructure and data pipelines for large-scale multidimensional imaging datasets, including OME-TIFF, Zarr, and HDF5.
• Optimize GPU memory usage, batching, inference throughput, architecture, code quality, and MLOps processes.

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.
• Expert knowledge of machine learning theory, image processing fundamentals, object detection, instance segmentation, and quantitative image analysis.
• Demonstrated experience with high-dimensional scientific imaging data, including fluorescence or brightfield microscopy, digital pathology whole slide images, high-content screening, or multiplexed imaging.
• Strong knowledge of GPU acceleration, parallel computing, CUDA, and ML performance optimization for large image datasets.
• Experience with Kubernetes, relational and NoSQL databases, object storage, and cloud-native architectures in public clouds, ideally AWS.
• Understanding and application of software engineering best practices, CI/CD, and MLOps principles.
• Excellent communication skills, trusted partnership-building, ability to learn new technologies and domain knowledge quickly, and willingness to acquire new programming languages.

Nice to have

• Experience with multimodal 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, or AI agents.

Culture & Benefits

• Collaborative work across computational scientists, biologists, bench scientists, AI/ML experts, product leaders, software engineers, and bioimage analysts.
• Opportunity to contribute to life-changing treatment discovery and development through scientific imaging and AI.
• Benefits are available as detailed in the company benefits information.
• Equal opportunity employment and applicant accommodation support are provided.