Model Development: Design, implement, and optimize machine learning models with a primary focus on Computer Vision applications.
Deployment Optimization: Build and maintain efficient deployment pipelines for ML models on CPU-based cloud servers (e.g., Azure), with occasional GPU-based deployments for resource-intensive tasks.
Performance Tuning: Optimize AI containers and applications for speed, scalability, and resource efficiency.
Collaboration: Partner with data scientists, engineers, and product managers to integrate ML solutions seamlessly into business workflows.
Performance Monitoring: Continuously monitor the performance of deployed models, troubleshoot issues, and implement improvements to ensure reliability and accuracy.
Documentation: Create and maintain clear, comprehensive documentation for model development, testing, and deployment processes.

AI ML Engineer

Job Description