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Edge Machine Learning Developer

3 weeks ago

Bengaluru, Karnataka, India beBeeEngineering Full time US$ 1,20,000 - US$ 1,55,000
Machine Learning Engineer for Edge Devices
A cutting-edge team responsible for building innovative solutions that enhance efficiency through data-driven insights. We optimize processes, reduce waste, and improve productivity by leveraging advanced analytics and AI-driven technologies.
You will be responsible for the end-to-end deployment of machine learning models on edge devices, taking ownership of all aspects of edge deployment, including model optimization, scaling complexities, containerization, and infrastructure management, ensuring high availability and performance.

Key Skills & Qualifications
  • Lead the entire edge deployment lifecycle, from model training to deployment and monitoring on edge devices.
  • Develop and maintain a scalable Edge ML pipeline that enables real-time analytics at various sites.
  • Optimize and containerize models using Portainer, Docker, and Azure Container Registry (ACR) to ensure efficient execution in constrained edge environments.
  • Own and manage the GitHub repository, ensuring structured, well-documented, and modularized code for seamless deployments.
  • Establish robust CI/CD pipelines for continuous integration and deployment of models and services.
  • Implement logging, monitoring, and alerting for deployed models to ensure reliability and quick failure recovery.
  • Ensure compliance with security and governance best practices for data and model deployment in edge environments.
  • Document thought processes and create artifacts on team repositories/wiki for knowledge sharing and sign off.
  • Review code quality and design developed by peers.
  • Improve the performance and reliability of code that creates high-quality and reproducible results.
  • Develop internal tools/utils that improve productivity across the team.
  • Collaborate with other team members to advance the team's ability to ship high-quality code fast.
  • Mentor/coach junior team members to continuously upskill them.