Senior MLOps Engineer

Job Description

As a Senior MLOps Engineer, you will be part of a cutting-edge team that is revolutionizing real-time AI and video applications.

Responsibilities

• Design and optimize ML pipelines for training, validation, and inference.
• Automate deployment of deep learning and generative models for real-time use.
• Implement versioning, reproducibility, and rollback capabilities.
• Deploy and manage containerized ML solutions on cloud platforms (AWS, GCP, Azure).
• Optimize model performance using tools such as TensorRT, ONNX Runtime, and PyTorch.
• Work with GPUs, distributed computing, and parallel processing to power AI workloads.
• Build and maintain CI/CD pipelines using tools like GitHub Actions, Jenkins, ArgoCD.
• Automate model retraining, monitoring, and performance tracking.
• Ensure compliance with privacy, security, and AI ethics standards.

Job Highlights

(This section is to be filled with specific highlights, benefits, or key aspects of the role provided by the employer).

Skills & Technologies

• Machine Learning Pipelines
• Containerization (Docker, Kubernetes)
• Cloud Platforms (AWS, GCP, Azure)
• ML Optimization Tools (TensorRT, ONNX, PyTorch)
• CI/CD Tools (GitHub Actions, Jenkins, ArgoCD)
• GPU Computing

Note: Replace the Job Highlights placeholder with actual highlights or key points provided.

Job Highlights

• Cutting-edge AI and video applications
• Work with top cloud platforms and ML optimization tools
• Automate deployment and scaling of ML models
• Focus on real-time inference and system performance
• Maintain high standards of privacy and security