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Salary
$245k – $295k per year
Location
Remote/Hybrid (San Francisco, United States)
Seniority
Senior · 8+ years exp
Employment
Full-Time
Overview
Company
Impact
Profile match
Gridware builds sensing technology that detects faults on electricity distribution networks. Its pole-mounted devices identify conductor failures before they cause fires. Utilities deploy the sensors across high-risk network areas.

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
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