United States
National Center for Urban Solutions
Sense
Cambridge, Massachusetts, United States
Senior Machine Learning Engineer - Active
Sense is a climate tech company that turns electric signals in homes and on the grid into real-time insight about energy use, devices, and faults. These insights help people lower their electric bills and use less electricity, and they help utilities prevent wildfires, among other applications. These insights come from load disaggregation and fault detection models that are running on meters today. The technology team at Sense researches, trains, deploys, and supports these models.
We are looking for an experienced Senior Machine Learning Engineer with expertise in active learning systems to help us scale our data operations so we can continue to improve our core production models and build the foundation model of electrical devices and energy.
This Senior Machine Learning Engineer will own the loop from data to labels to improved models. You will use active learning and weak supervision methods to generate labels, decide what to label next, and turn errors we find in the field into new labels.
This is a hands-on role. You will be expected to write code, train models, analyze data, and document experiments. You will work with data scientists, annotators, product, and engineers to get labels and improve models. You will direct the development of annotation tools and the work of our annotators to speed up and scale labeling.
Success in this role is measured by the reduction in cost per annotation (i.e., time per annotation), while keeping label quality at or above our targets.
Location: able to work from our Cambridge, MA office at least 2 days per week.
Salary range: $165,000 to $185,000
Work authorization: required.
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