Senior Engineer- Machine Learning

## Senior Engineer
- Machine Learning Apply:
Milwaukee, WI:
Full time:
Posted Today:
4630### Badger Meter - Where Every Drop Counts and So Do You At Badger Meter, we're more than a leading global water technology company - we're innovators with a mission: to preserve and protect the world's most precious resource. For over
** 120
* * years, our trusted solutions have enabled our customers to optimize the delivery and use of water, maximize revenue and reduce waste.

Every employee at Badger Meter is an important part of our success. Here, your work doesn't just move a business forward - it shapes a more sustainable future. We are committed to building a workplace where we celebrate differences, empower voices, and encourage fresh ideas that drive innovation.

When you join us, you'll find:
* ** Purpose-driven work
** that makes a real difference in communities around the globe.
* ** Career growth and development opportunities
** designed to help you achieve your potential.
* ** A supportive, inclusive*
* ** culture
* * where collaboration and creativity  part of something bigger. At Badger Meter, your contributions will ripple far beyond the workplace - creating lasting change for people and the planet.### What You Will Contribute:### # Senior Engineer, Machine Learning  
** Job Description
** The Senior Engineer, Machine Learning is a mid-career position of independence and ownership of large investigations and projects. The Senior Engineer will define the scope and tasks for machine learning initiatives and may perform the efforts themselves or with one or more engineers assisting. The successful candidate will possess strong knowledge of modeling techniques and system performance, and be able to define resources and time needed to estimate project efforts.

This role focuses on the design, development, testing, validation, deployment, and ongoing tuning of machine learning pipelines and models that support product performance, installation quality, and outage detection, as well as fleet-wide health monitoring of the deployed population of millions of meters, sensors, radios, connectivity equipment, and other IoT devices in support of the Systems Integration team, and also encompasses the data infrastructure, integration, and monitoring systems that keep those models reliable  Senior Engineer is expected to contribute quickly to the team's portfolio of algorithms, ML models, and AI tools, creating predictive models, classifiers, time series data mining, and anomaly detection algorithms, and will work closely with developers, data engineers, data scientists, and reliability, quality, and design engineering to identify and address product weaknesses.

The Senior Engineer will represent the team on projects and investigations, report findings to leadership, and act as a mentor to other engineers.  
** ESSENTIAL

JOB DUTIES:

***** Leadership & Scope-Setting
**** Act as project lead engineer for machine learning initiatives; may lead a technical team
* Define the scope of machine learning projects and investigations; develop or provide input to schedules and budgets
* Define and control model design standards and validation criteria
* Mentor other engineers, including guidance on data ingestion, cleaning, and model development practices
* Provide oversight of model performance dashboards, ML-driven product support issues, and customer-impacting model behavior
*** ML Pipeline & Model Lifecycle
**** Design, build, and maintain end-to-end machine learning pipelines, from data preparation through training, validation, deployment, and production monitoring
* Develop, tune, and maintain predictive models, classifiers, and AI tools, such as installation quality and outage detection models, to improve accuracy and reliability
* Develop time series data mining and anomaly detection algorithms to monitor the health and performance of millions of deployed meters, sensors, radios, and IoT devices
* Recommend corrective actions and trigger field responses, or hand off findings to design and reliability engineers
* Establish testing and validation frameworks to confirm model outputs against real-world data, including coordinating field or manual verification studies
* Monitor deployed models for drift, degraded performance, or unexpected outcomes, and lead remediation efforts
* Support integration of model outputs into customer-facing dashboards and reporting tools
* Identify opportunities to improve existing infrastructure, workflows, products, and investigations with…