Senior Applied Scientist, Gridware

ML DSP

Salary not provided

Mid and Senior level

San Francisco Bay Area

Enhancing grid assets with cutting-edge technology

Job no longer available

Enhancing grid assets with cutting-edge technology

21-100 employees

B2BEnergyAnalyticsSaaS

Job no longer available

Salary not provided

Mid and Senior level

San Francisco Bay Area

21-100 employees

B2BEnergyAnalyticsSaaS

Company mission

To create a future where power outages and electrical grid hazards (think wildfire ignition) are a thing of the past.

Job

Company

Role

Who you are

The ideal candidate will possess deep knowledge of machine learning architectures, digital signal processing techniques, and algorithm design
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

What the job involves

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
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

Our take

Utilities struggle with old infrastructure, which can cause long outages and increase wildfire risks. Current methods to address these issues are slow and costly, making it hard for utilities to keep up with necessary upgrades and risk management.

To tackle these problems, Gridware has created an affordable, easy-to-install technology that works with existing utility systems. It provides real-time data on infrastructure and wildfire risks, helping utilities reduce outages and spot potential wildfire threats easily.

Since launching, Gridware has expanded to five states and collected over one million hours of data. To support this growth, the company recently closed a successful funding round. With this financial support, Gridware is ready to help more widely improve utility reliability and wildfire prevention.

Freddie

Company Specialist at Welcome to the Jungle

Company

Funding (last 2 of 3 rounds)

Jan 2025

$26.4m

SERIES A

Jun 2023

$10.5m

SEED

Total funding: $42.2m

Company benefits

Flexible starting hours to reduce commute
Health, Dental & Vision (Gold and Platinum plans fully covered)
Paid Parental Leave
Company-paid training to upgrade your skills
Free parking and a commuter allowance

Company HQ

West Oakland, Oakland, CA

Leadership

Timothy Barat

(CEO)

Graduated from UC Berkeley College of Engineering with an MS in Electrical Engineering and Computer Science. Was a Graduate Student Researcher for 2 years.

Hall Chen

(CTO)

Graduated from UC Berkeley with a BS in Electrical Engineering and Computer Science. They previously worked as an RF Payload Designer at Astranis.

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