About the job
Key Responsibilities
• Infrastructure Development: Architect, set up, and oversee containerized GPU deployments utilizing Docker.
• Multi-modal Project Execution: Seamlessly integrate and deploy machine learning models tailored for audio, video, and image processing applications.
• Framework Collaboration: Work closely with data science teams to facilitate the integration of TensorFlow, Keras, and other deep learning frameworks into production workflows.
• Kubernetes Optimization: Enhance and manage Kubernetes clusters to ensure scalable and efficient model deployment.
• Model Performance Optimization: Employ ONNX and C-based frameworks for highly efficient model execution and scalability.
• Continuous Model Monitoring: Track model performance, identify model drift, and ensure the stability of deployed models in operational environments.
• End-to-End Pipeline Support: Assist with comprehensive machine learning pipelines, from initial data ingestion to final model deployment.
• Cross-team Collaboration: Foster effective communication among cross-functional teams to align on project objectives and deliverables.
