Senior Applied Scientist, ML DSP

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Job description

Gridware exists to enhance and protect the mother of all networks: the electrical grid. The grid touches everything, and when it grinds to a halt, the consequences can be dire: wildfires burn, land is destroyed, property is damaged, progress stops, and lives are lost.

Our team engineers an advanced sensing system to continuously analyze both the electrical and mechanical behavior of grid assets. Utilizing high-precision sensor arrays, the system identifies and allows preemptive mitigation of faults. The technology has been proven with utilities to bolster safety, reliability, and reduce customer outage durations. The demand for power will only increase. We protect the grid of today while we build the grid of tomorrow.

Gridware is privately held and backed by the best climate-tech and Silicon Valley investors. We are headquartered in the Bay Area in northern California.

Role Description:

The Senior Applied Scientist specializing in ML DSP (Machine Learning with Digital Signal Processing) is responsible for evaluating and developing models for multimodal time series sensor data on heavily resource-constrained computation systems. The ideal candidate will possess deep knowledge of machine learning architectures, digital signal processing techniques, and algorithm design.

Responsibilities:

The Senior Applied Scientist will, as a starting point, be responsible for the following:

Execute end-to-end ML projects from exploratory data analysis to feature engineering and model evaluation, and inform firmware implementation and deployment.

Design and build physically-informed data augmentation and domain randomization algorithms.

Conduct literature reviews and research on resource-constrained inference and training techniques.

Work closely with cross-functional teams, including hardware engineers, firmware engineers, and product managers.

Required Skills:

Computer Science or Electrical Engineering degree

4+ years of professional experience with production machine learning models

4+ years of professional experience with physical sensors and time series data modeling

4+ years of research experience

Experience low-level languages and memory management

Strong fundamentals in statistics and computer science

We encourage you to apply even if you don't have all of the bonus skills listed above. We believe diverse perspectives drive innovation and growth.

Benefits:

Flexible hours / hybrid schedule for those in the Bay Area

Health, Dental & Vision (Gold and Platinum plans fully covered)

Paid parental leave

Commuter allowance

Company-paid training

Gridware is an equal opportunity employer. We want applicants of diverse backgrounds and hire without regard to color, gender, religion, national origin, citizenship, disability, age, sexual orientation, or any other characteristic protected by law.

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