MLOps Enginieer

About the job
The MLOps engineer should have 5+ years of experience in Python Pandas, Spark and will have experience building large-scale data pipelines
Experience in Seldon, Triton, Jenkin CI/CD
One year of experience in Big data technologies such as BigQuery, Hadoop, SQL, Hive, GCP/Azure, Java, REST (nice to have)

In Your Day-to-day Responsibilities

Design & create the data pipelines and engineering infrastructure to support our clients’ enterprise machine learning systems at scale
Take models that data scientists built and turn them into a machine learning production system
Develop and deploy scalable tools and services for our clients to handle machine learning training and inference
Identify and evaluate new technologies to improve the performance, maintainability, and reliability of our clients’ machine learning systems
Apply software engineering rigor and best practices to machine learning, including CI/CD, automation, etc.
Support model development with an emphasis on auditability, versioning, model measurement and data security
Interpret the results of the models, read data on a fundamental level, and understand how it relates to the problem being solved by the model.
Monitor the performance of your models, and need to be able to troubleshoot any errors or bugs that may occur.