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Senior ML Ops / Data Engineer

We are looking for highly talented, creative, and passionate Senior ML Ops / Data Engineer to join us.

OutSense Diagnostics is an Israeli based company that has developed an advanced technology for early detection of medical conditions. The IoT technology analyzes and diagnoses human waste from within a standard toilet bowl, and alerts caregivers of health deviations. The company’s database enables highly personalized care 

 ?What are we looking for

A Senior ML ops Engineer with a strong background with experience in Deep learning in production environments to drive the deployment and improvement of our algorithms

In this role, you’ll be expected to collaborate closely with both software and cloud development teams, deploy new models into our cloud infrastructure, manage and maintain our algorithm pipeline and integrate the algorithms into the cloud

The position demands a unique combination of deep technical knowledge in machine learning and a solid understanding of cloud-based deployment

We are looking for open-minded, entrepreneurial candidates who intend to use their skills to enhance global wellness and health

Key Responsibilities

  • Maintenance of Cloud-based Platform: Regularly monitor and maintain the operational  of our cloud-based annotation and training platform
  • Model Training and Enhancement: Train new models as required, ensuring high accuracy and efficiency. Update and optimize existing models to keep up with changing requirement
  •  Code Management: Work with Git repositories to manage and update codebase as necessary
  • Collaboration: Work closely with the development teams and cloud team to integrate new features and improvements into the existing system
  • Algorithm Development: Develop and refine image analysis algorithms

 

:What you bring to the team

  • MSc-Bsc  in Computer Science, Computer Engineering, or related field
  • 3+ years experience in deploying deep learning algorithms in a production environment  
  • In depth understand of Python and Pytorch
  • Strong experience with AWS, particularly in deploying and managing machine learning workloads
  • Skilled in managing and optimizing machine learning pipelines, ensuring they are efficient, scalable, and reliable
  • Deployment of vision algorithms in AWS
  • Demonstrated ability to deliver in a fast-paced environment
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