MLOps or DevOps for Machine Learning allows to combine the efforts of Data Scientists, Data Engineers and support specialists to increase the speed, quality of development and deployment of ML models. Being inspired by the principles of DevOps, MLOps solutions take care of automation of the whole ML lifecycle so that businesses can get what they need seamlessly, which is their business values.
Our experienced team of MLOps engineers will ensure automation of model training process, reproducibility of training results, efficient feature engineering, smooth model deployment, scalability and robust production use.
TECH STACK: Python, R, Spark, Tensorflow, pyTorch, MLflow, Kubeflow, Pandas, Databricks, Seldon, Jupyter, CEPH, Feast, Grafana, Prometheus, Apach Spark, Apache Airflow, Helm, Argo, Git, Jaeger