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Gridware

Senior Applied Scientist, DSP/ML

Join Gridware in San Francisco as a Senior Applied Scientist specializing in ML and DSP. Develop efficient models for edge devices under strict resource limits. Enjoy benefits like paid parental leave and a unique two-week paid break called 'Off the Grid.'
Gridware
Gridware
San Francisco, California, United States On-site Full time USD 170k–205k yearly UTC-08:00

Gridware

Company Overview

Gridware

California, United States

2020

Approximately 30 employees (source: businessinsider.com).

What They Do

Gridware is a pioneering startup focused on enhancing grid resilience through innovative technology. Their core offering, Active Grid Response (AGR), utilizes pole-mounted Gridscope sensors that monitor various conditions on distribution power lines in real-time. These sensors are powered by solar energy and communicate through device-to-device, cellular, and satellite networks, ensuring continuous operation regardless of grid voltage (source: gridware.io). The technology is designed to detect a range of issues, including vegetation contact, downed lines, and equipment failures, enabling utilities to perform predictive maintenance and dynamic de-energization to prevent wildfires and outages (source: cbsnews.com). Target markets include U.S. electric utilities, particularly in wildfire-prone areas like California and the Midwest, with plans for international expansion in the future (source: promptloop.com). Their products integrate seamlessly with utility operations management systems, covering over 90 million field hours and serving 40% of U.S. customers through partnerships (source: gridware.io).

Projects & Track Record

Gridware has successfully deployed approximately 13,000 sensors across eight states, particularly in California's high-risk wildfire areas, covering around 1,000 miles of power lines. Their technology has been credited with preventing wildfires, as evidenced by reports of alerts that stopped smoldering vegetation from igniting (source: cbsnews.com). Notable integrations include partnerships with PG&E for high impedance fault detection and a pilot project with Puget Sound Energy aimed at improving storm and wildfire repair prioritization. In one instance, a Northern California circuit experienced a 70% reduction in outage patrol times, while a Midwest utility saved 400,000 outage minutes across four circuits (source: gridware.io). Ongoing projects include a 2024 pilot with NorthWestern Energy in Montana City, focusing on real-time asset monitoring to mitigate wildfire risks (source: northwesternenergy.com).

Recent Developments

In the past two years, Gridware has raised significant funding to support its growth and expansion efforts. In 2024, they announced a $26.4 million Series A funding round led by Sequoia Capital, following a $10.5 million seed extension in 2023 co-led by Lowercarbon Capital and Fifty Years (source: gridware.io). This funding is aimed at enhancing their U.S. operations and preparing for international deployments. Additionally, Gridware has received recognition for its innovative technology, including being named one of Time magazine's Best Inventions in 2022 for their Gridscope sensors and having founders featured in Forbes 30 Under 30 in 2023 (source: engineering.berkeley.edu). The company continues to deepen its partnerships with utilities, including a pilot program with NorthWestern Energy set for late 2024 (source: northwesternenergy.com).

Working There

Gridware offers a variety of engineering-focused roles, including positions in software engineering, electrical design engineering, data engineering, and technical recruiting. The company is built by linemen and engineers, reflecting a culture that emphasizes collaboration with field workers and a mission-driven approach to wildfire prevention (source: climatepeople.com). Hiring is concentrated at their Bay Area headquarters, where they are rapidly expanding their team to support sensor production and deployment efforts. The culture at Gridware is described as rigorous and mission-oriented, with a strong focus on achieving real-world results, such as the significant field hours logged by their technology (source: gridware.io). While specific employee benefits are not detailed in the sources, the venture-backed nature of the company suggests competitive startup perks may be available (source: cbsnews.com).


Last updated on Feb 23, 2026 | Report an issue

We are seeking a Senior Applied Scientist with expertise in machine learning and digital signal processing (DSP) to design models that operate on multimodal time-series sensor data in highly resource-constrained environments. You will develop algorithms that balance accuracy with strict power and memory limits, helping advance the next generation of Gridware's edge intelligence. This role blends applied research, model optimization, and low-level implementation in collaboration with hardware and firmware teams.

Responsibilities

  • Execute end-to-end ML workflows, including exploratory data analysis, feature engineering, model training, evaluation, and optimization.
  • Design and evaluate machine learning and DSP algorithms that meet strict power, memory, and latency constraints on embedded hardware.
  • Conduct research and literature reviews on edge ML, resource-constrained inference, and efficient training techniques.
  • Partner closely with hardware, firmware, and product teams to ensure seamless integration of models into the full system.

Required Skills

  • MS or PhD in Computer Science, Electrical Engineering, or a related technical field.
  • 3+ years of experience developing and deploying production ML models.
  • 3+ years of applied research experience in ML, DSP, or algorithm development.
  • Hands-on experience working with physical sensors and modeling time-series data.
  • Strong foundation in ML architectures, DSP theory, and algorithm design for real-world systems.

Bonus Skills

  • Experience developing or optimizing algorithms in C/C++ for resource-constrained embedded systems.
  • Experience porting ML models from Python frameworks to firmware-level implementations.
  • Familiarity with edge ML tools, quantization, model compression, or on-device inference strategies.

$170,000 - $205,000 a year

At this time, Gridware is unable to provide visa sponsorship or immigration support for this role. We're only able to consider candidates who are currently authorized to work in the country of employment without visa sponsorship now or in the future.

This describes the ideal candidate; many of us have picked up this expertise along the way. Even if you meet only part of this list, we encourage you to apply!

Benefits

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

Paid parental leave

Alternating day off (every other Monday)

"Off the Grid", a two week per year paid break for all employees.

Commuter allowance

Company-paid training

Apply now

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About the role

March 19, 2026

Full time

Company

March 19, 2026

On-site

USD 170k–205k yearly

Smart Grid

Gridware

gridware.io

  •  San Francisco, California, United States

3+ years

UTC-08:00