Senior Manager, Machine Learning

Gridware is a technology company focused on 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 mechanical 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 headquartered in San Francisco, California, and 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.

 

 

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 

• 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

• 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

• 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