Machine Learning Engineer

Company Description:

At HOPPR, we empower developers to build the next generation of AI medical imaging applications, with the goal of making clinical care and workflow optimization more accessible, efficient, and equitable within the healthcare systems they serve.

Role Description:

The Machine Learning Engineer will collaborate with researchers, engineers, and clinicians to design and deploy scalable machine learning solutions, building shared ML infrastructure and optimizing models for production. This role requires a blend of technical expertise, problem-solving skills, and the ability to integrate machine learning solutions into enterprise-grade products, driving innovations that improve patient care.

Key Responsibilities:

• Develop, deploy, and maintain state-of-the-art machine learning models for medical imaging, NLP, and multimodal tasks.
• Design and implement robust, scalable ML pipelines and shared infrastructure to support agile experimentation and deployment.
• Collaborate with researchers to translate novel algorithms into production-ready solutions.
• Build and maintain MLOps tools and practices, including automated testing, continuous integration, and monitoring of deployed models.
• Optimize model performance for speed, reliability, and scalability in production environments.
• Partner with clinicians, engineers, and product teams to align machine learning efforts with clinical and product needs.

Minimum Qualifications:

• Bachelor’s degree in Computer Science, Engineering, or a related field with 5+ years' experience in relevant roles.
• Proficiency in Python and machine learning frameworks.