Machine Learning Engineer

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.

As a Staff ML Engineer, you will work directly in Gridware’s Automation org and play a critical role in helping shape and execute on developing algorithms to help improve the speed and accuracy at which Gridware identifies hazards on the grid.

$230,000 - $250,000 a year

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!

• Design, implement, and deploy advanced machine learning models operating on multi‑modal and multi‑resolution data
• Lead development 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
• Partner with software engineering and ML infrastructure teams to ship robust, production‑grade ML systems
• Act as a technical leader and reviewer across Machine Learning and Data Science teams, influencing architecture and modeling decisions
• Mentor and support junior engineers and scientists through design reviews, pairing, and technical guidance
• Explore and evaluate novel modeling approaches and research ideas to address existing and emerging automation challenges

• 8+ years of experience building and deploying machine learning models in production environments
• Deep 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
• Familiarity with human‑in‑the‑loop or human‑on‑the‑loop ML systems

• 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