Machine Learning Architect

You should possess a minimum of 7-10 years of industry experience, out of which a minimum of 5 years should have been in machine learning roles. Your proficiency in Python and popular ML libraries such as TensorFlow, PyTorch, and Scikit-learn should be advanced. Furthermore, you should have hands-on experience in distributed training, model optimization including quantization and pruning, and inference at scale. Experience with cloud ML platforms like AWS (SageMaker), GCP (Vertex AI), or Azure ML is essential. It is expected that you are familiar with MLOps tooling such as MLflow, TFX, Airflow, or Kubeflow, and data engineering frameworks like Spark, dbt, or Apache Beam. A solid understanding of CI/CD for ML, model governance, and post-deployment monitoring (e.g., data drift, model decay) is crucial for this role. In addition to technical skills, problem-solving abilities, effective communication, and strong documentation skills are highly valued in this position.,