Machine Learning (Remote)

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.