We are looking for someone to help us keep our machine learning models running smoothly in production. Your job will be to monitor for issues like model drift and data drift, ensure models stay accurate, and integrate tools like WhyLabs, Splunk, and Datadog
What You Will Do
Monitor machine learning models for issues like data/model drift
Set up tools like WhyLabs, Splunk, and Datadog to track model performance
Work on the full lifecycle of models, including deployment, monitoring, and retraining
Help improve how we manage and monitor data pipelines
Collaborate with the team to make sure models stay accurate and useful
What We are Looking For
Experience monitoring machine learning models in production
Knowledge of tools like WhyLabs, Splunk, and Datadog
Familiarity with AKS and Databricks
Understanding of how data moves through systems and how to keep it reliable
Comfortable with Python or SQL for debugging and building workflows
Understanding of MLOps best practices.
Experience with cloud tools like Azure Cosmos DB
Familiarity with integrating models into BI tools for reporting.
ABOUT CAPGEMINI
At Capgemini Engineering, the world leader in engineering services, we bring together a global team of engineers, scientists, and architects to help the world’s most innovative companies unleash their potential. From autonomous cars to lifesaving robots, our digital and software technology experts think outside the box as they provide unique R&D and engineering services across all industries. Join us for a career full of opportunities. Where you can make a difference. Where no two days are the same. #LI-Hybrid #LI-LG6