Seeking a MLOps with 10 - 15 years of engineering experience to design end-to-end MLOps platforms and bring machine learning models to production at scale.
Key Responsibilities :
- Build end-to-end MLOps systems for continuous model training, monitoring, drift detection, and automated deployment.
- Design real-time inference pipelines and batch scoring architectures for deep learning and ML models.
- Optimize model inference latency, hardware resource utilization (GPUs/TPUs), and cloud ML infrastructure costs.
- Implement data security, privacy, and regulatory compliance standards across the ML lifecycle.