HOPPR is looking to integrate their multimodal AI foundation models into radiological clinical software for their partners, requiring assistance with model fine-tuning, prompt engineering, and pre-sales activities.
Requirements
- Strong programming skills (Python, C++, or similar).
- Experience with cloud environments (OCI, AWS, Azure, GCP).
- Knowledge of ML frameworks (PyTorch, TensorFlow) and deployment tools (Docker, Kubernetes).
- Familiarity with data pipelines, distributed systems, or ML deployment.
- Comfort with APIs, SDKs, and integration of third-party systems.
- Experience in medical imaging (DICOM, PACS, radiology workflows) desired.
Responsibilities
- Work side-by-side with clinical, research, and industry partners to understand their imaging AI challenges.
- Translate clinical workflows and regulatory requirements into technical specifications.
- Serve as the technical face of HOPPR during deployments.
- Build and customize pipelines to support AI model fine-tuning, validation, and deployment.
- Write production-grade code to integrate APIs, data pipelines, and ML models into customer systems.
- Prototype rapidly while ensuring scalability and compliance.
- Troubleshoot integrations across hospital PACS, cloud infrastructure, and enterprise systems.
Other
- Ability to navigate ambiguity, adapt quickly, and deliver solutions in unstructured environments.
- Strong communication skills and ability to engage technical and non-technical stakeholders.
- Willingness to travel to customers when needed.
- This opportunity is open exclusively to US citizens and permanent residents.
- Bachelor’s or Master’s degree in Computer Science, Electrical or Biomedical Engineering, Applied Mathematics, or a related technical field.
