ML Engineer
Job Summary
Proficiency in Pyspark
Experience with working on Delta lake storage in Azure Databricks
Secondary skills
Proficiency in ML frameworks (e.g. TensorFlow PyTorch Scikit-learn).
Experience with model deployment tools (e.g. MLflow Kubeflow SageMaker).
Strong understanding of model serving A/B testing and performance monitoring.
Familiarity with CI/CD for ML containerization (Docker) and orchestration (Kubernetes).
Knowledge of real-time data processing and inference (Kafka Flink Spark Streaming).
Experience with working on Delta lake storage in Azure Databricks
Secondary skills
Proficiency in ML frameworks (e.g. TensorFlow PyTorch Scikit-learn).
Experience with model deployment tools (e.g. MLflow Kubeflow SageMaker).
Strong understanding of model serving A/B testing and performance monitoring.
Familiarity with CI/CD for ML containerization (Docker) and orchestration (Kubernetes).
Knowledge of real-time data processing and inference (Kafka Flink Spark Streaming).