MLOps Lead - Machine Learning Models

MLOps Lead :

Role Overview :

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.

Technical Skills :

- PyTorch, TensorFlow, MLflow, Kubeflow, Feast (Feature Store), Triton Inference Server, Docker, Kubernetes, Python, C++.

Leadership Focus :

- Production ML governance, scalable MLOps strategy, bridging data science with core software engineering teams.