Gridware

Senior Manager, Machine Learning

San Francisco, California, U.S.

Full-Time

Hybrid

$245,000 – $295,000 per year

TLDR

Lead cloud sensor modeling strategy, build production-grade ML systems, and improve automated hazard detection through algorithms and data strategy.

About Gridware

Gridware is a San Francisco-based technology company dedicated to protecting and enhancing the electrical grid. We pioneered a groundbreaking new class of grid management called active grid response (AGR), focused on monitoring the electrical, physical, and environmental aspects of the grid that affect reliability and safety. Gridware’s advanced Active Grid Response platform uses high-precision sensors to detect potential issues early, enabling proactive maintenance and fault mitigation. This comprehensive approach helps improve safety, reduce outages, and ensure the grid operates efficiently. The company is backed by climate-tech and Silicon Valley investors. For more information, please visit www.Gridware.io.

Role Description

As a Senior ML Manager, you will serve as a player coach role for Gridware’s cloud-based modeling team. You will help grow the existing team, improve algorithmic development frameworks, focus on strategic initiatives and direction for how we approach cloud sensor modeling, and establish best practices for a high throughput ML team.

Responsibilities

70% team management and strategy, 30% IC time

Grow a high-performing team through hiring, coaching, performance management, and career development

Partner with software engineering and ML infrastructure teams to ship robust, production-grade ML systems

Own technical roadmap and execution for the cloud ML organization, balancing near-term product delivery with long-term technical investments

Lead technical design of algorithms that improve the speed, accuracy, and reliability of Gridware’s automated hazard detection systems

Define data strategy and labeling requirements, including real-world data collection and synthetic data generation approaches

Explore and evaluate novel modeling approaches and research ideas to address existing and emerging automation challenges

Required Skills

3+ years of direct management experience

8+ years of experience building and deploying machine learning models in production environments

Experience with both deep learning and classical machine/statistical learning techniques

Strong programming skills with demonstrated proficiency in Python

Experience working within modern software stacks, including cloud platforms, containerization, and CI/CD workflows

Bonus Skills

Experience working with signal processing or sensor-derived data

Experience at a growth-stage start-up

Familiarity with human-in-the-loop or human-on-the-loop ML systems

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!

Gridware Technologies Inc. is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to any characteristic protected by applicable federal, state, or local law.

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

Benefits

Health Insurance

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

Company-paid training

Paid Parental Leave

Paid Time Off

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

Gridware

Gridware builds advanced technology for the electrical grid, specifically through its Active Grid Response platform that utilizes high-precision sensors for real-time monitoring. Targeting utility companies, this innovative system helps detect potential disturbances early to prevent outages and enhance the safety and reliability of critical infrastructure.

Founded: Founded 2020
Employees: 51-200 employees
Industry: computer software
Funding stage: Series B
Total raised: $97M raised
Last funding: Raised November 2025

Enterprise Software

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Machine Learning Engineer