remote
AI Architect Deep Learning - Vanquish Bio
ML Engineer
Design and lead development of deep‑learning models for real‑time cancer detection in medical imaging, handling multimodal data, model training, validation, and regulatory compliance.
About the role
Key Responsibilities
- Architect, develop, and optimize deep‑learning pipelines for real‑time detection of solid tumors, cysts, and normal tissue across multiple imaging modalities.
- Lead data preprocessing, annotation, and augmentation strategies specific to medical imaging datasets.
- Implement and fine‑tune models using frameworks such as TensorFlow and PyTorch, ensuring high accuracy and low latency for point‑of‑care use.
- Collaborate with cross‑functional teams to integrate AI outputs into the clinical workflow and support FDA SaMD clearance efforts.
- Establish robust training, validation, and continuous monitoring processes, including performance tracking on cloud platforms like AWS.
Requirements
- 5+ years of experience building and deploying deep‑learning solutions, preferably in medical imaging or related healthcare domains.
- Strong proficiency in Python and deep‑learning frameworks (TensorFlow, PyTorch).
- Hands‑on experience with multimodal data fusion, model optimization for real‑time inference, and cloud services (AWS).
- Familiarity with regulatory standards for AI‑driven medical devices (FDA SaMD, IEC 62304) and ability to produce validation documentation.
- Excellent problem‑solving skills, ability to work independently, and strong communication for interdisciplinary collaboration.
Skills
pythontensorflowpytorchaws