Gesund.ai
Website:
gesund.ai
Job details:
We are 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.
Responsibilities
Job Description
- Help conceptualize and build an MLOps platform around data management and federated learning; from initial design to full implementation and deployment
- Work with the team to design and implement tools and APIs for a centralized system with distributed agents/workers
- Build supplementary software components that enables data scientists to interact with the platform
- Support integration with existing ML/DL/FL libraries
- Develop highly scalable machine learning (computer vision) models to solve problems such as medical image classification and segmentation
- Develop in-house machine learning tools and pipelines to support fast experimentation of machine learning models
- Work with other engineers to identify and solve machine learning problem
Requirements
- Experience in one or more of the following areas: deep learning, computer vision,
- Experience with machine learning frameworks such as TensorFlow, PyTorch or YOLO
- Curiosity and minimal experience in Federated Learning & Self- Supervised Learning algorithms & applications
- Expert knowledge in Python (object oriented design)
- Expertise in API design with FastAPI
- Through understanding of deploying ML models via Docker and Kubernetes at scale on-prem and cloud.
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