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Frontend Developer (Remote)

Gesund Ai — United States · Posted ~22 hours ago

Full-time Remote

Skills

React.js Frontend Development Dashboard Development Analytics Tools Integration ML Team Collaboration

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Summary ✨ AI‑Generated

We are building a privacy-first MLOps platform designed for data-driven organizations in healthcare and life sciences. Seeking a Frontend Developer with strong React.js skills to develop user-facing components and implement them using established workflows. The successful candidate will work closely with ML teams, data analytics platforms, and visualization tools to build robust, maintainable dashboards and analytics interfaces. This is an exciting opportunity to contribute to cutting-edge medical research by enabling scalable solutions that bring clinical-grade ML applications to market.

Highlights

Develop user interfaces for a privacy-focused MLOps platform, collaborate with ML teams, integrate analytics dashboards using React.js, and contribute to accelerating medical research through healthcare innovation.

Description

Gesund.ai is building a privacy-first MLOps platform for data-driven organizations in healthcare and life sciences. The platform is designed to support the entire lifecycle of machine learning (ML) efforts to accelerate breakthrough medical research and bring clinical-grade ML solutions to market. Our fast-expanding strategic network includes early clinical and technology partners and organizations in the US, Israel and Europe. Job Description Job Role The primary focus is on developing user interface components and implementing them following well-known React.js workflows (such as Flux or Redux). They work with ML teams, data analytics platforms, visualization & metrics tools (e.g. Grafana, Prometheus) and dashboards. They ensure that these components and the overall application are robust and easy to maintain. Responsibilities Developing new user-facing features and analytics dashboards using React.js,Integrating open-source templates & frameworks into production-grade codebase,Building reusable components and front-end libraries for future use,Optimizing components for maximum performance across a vast array of web-capable devices and browsers,Developing image viewers that have capacity to view medical image formats (such as dicom, nifti etc.), and develop a tool to handle interactive measurements and annotations (have the capacity of smart ways using computer vision) of these images,Developing image viewers that have capacity to view medical image formats (such as dicom, nifti etc.), and develop a tool to handle interactive measurements and annotations (e.g smart / AI-assisted pre-annotation using computer vision etc.)