What are the responsibilities and job description for the ML ( Machine Learning ) Engineers with Model Ops position at Russell Tobin?
What are we looking for in our ML ( Machine Learning ) Engineers with Model Ops?
Title: ML (Machine Learning) Engineer with Model Ops
Location: Seattle, WA
Duration: 12 Months
Pay Rate: $55/hr. - $60/hr.
ML Engineer - Model Ops
Looking for experience with Model Drift, Data Drift, and Model Monitoring. (this is a Model Ops Position – anything to do with the Model Lifecycle, all the monitoring capabilities are included here – Data Ops is also included)
In this space we are looking to integrate with WhyLabs
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
Title: ML (Machine Learning) Engineer with Model Ops
Location: Seattle, WA
Duration: 12 Months
Pay Rate: $55/hr. - $60/hr.
ML Engineer - Model Ops
Looking for experience with Model Drift, Data Drift, and Model Monitoring. (this is a Model Ops Position – anything to do with the Model Lifecycle, all the monitoring capabilities are included here – Data Ops is also included)
In this space we are looking to integrate with WhyLabs
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
- 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.
Salary : $55 - $60
