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PayPal Senior ML OPS Engineer United States, Ohio, Toledo 321349001
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This job requires creating new pipelines,
Your day to day
In your day-to-day role, you will
1. Design & create the data pipelines and engineering infrastructure to support our clients’ enterprise machine learning systems at scale
2. Take models that data scientists built and turn them into a machine learning production system
3. Develop and deploy scalable tools and services for our clients to handle machine learning training and inference
4. Identify and evaluate new technologies to improve the performance, maintainability, and reliability of our clients’ machine learning systems
5. Apply software engineering rigor and best practices to machine learning, including CI/CD, automation, etc.
6. Support model development with an emphasis on auditability, versioning, and data security
7. Facilitate the deployment of proof-of-concept machine learning systems
8. Communicate with clients to build requirements and track progress
9. Interpret the models' results, read data on a fundamental level, and understand how it relates to the problem the model is solving.
10. Monitor the performance of your models, and need to be able to troubleshoot any errors or bugs that may occur.
What do you need to bring:
- The MLOps engineer should have 5 - 8 years of experience in Python, Spark , Pandas and Apache Airflow.
- One year of experience in Big data technologies such as BigQuery, Hadoop, SQL, Hive, GCP & Azure
- One year of experience in Java, REST
- Experience in Seldon , Triton, Jenkin CI/CD
- Should have experience building large-scale data pipelines using Apache Kafka
Understand requirements.
High Level & Detailed design document.
Coding, Unit & Integration Testing.
Support during User Acceptance Testing.
Fix bugs identified during Testing and after deployment to Production.
Releasing the component to Production.
Post-production monitoring, ramp and support.
Our Benefits:
Any general requests for consideration of your skills, please
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