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.
Lead on-site or remote deployments, ensuring customer success.
Troubleshoot integrations across hospital PACS, cloud infrastructure, and enterprise systems.
Monitor system performance and optimize for reliability, speed, and compliance.
Partner with HOPPR’s product, ML research, software engineering and compliance teams to extend platform capabilities.
Bring customer feedback into product roadmaps, helping shape features that serve the broader market.
Contribute to documentation, demos, and developer resources for customers and internal teams.

Bachelor’s or Master’s degree in Computer Science, Electrical or Biomedical Engineering, Applied Mathematics, or a related technical field.
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.
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.
Experience in medical imaging (DICOM, PACS, radiology workflows) desired.

Forward Deployed ML Engineer

Key skills