Senior ML Engineer, Multi-Sensor Modeling
Gridware
Apply to this job San Francisco, CA hybrid Until 8/22/2026 5+ years exp First posted March 18, 2026 Last posted March 18, 2026
Job description
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.
Responsibilities
- Develop algorithms that improve the speed, accuracy, and reliability of Gridware’s automated hazard detection systems
- Work with multimodal time-series and spatial sensor data across diverse sampling rates and noise characteristics.
- Design models that are robust, interpretable, and deployable in production environments.
- Live in the data; help curate & share strategic & well-defined datasets that help solve our highest-value challenges
- Explore advanced approaches such as graph-based learning for grid topology reasoning, geospatial modeling and localization and multimodal fusion across acoustic, magnetic, vibration, electrical, and visual signals
- Write clean, scalable, well-tested Python code that integrates into a large shared codebase.
- Build end-to-end ML pipelines including data processing, feature extraction, training, evaluation, and deployment.
- Optimize models for performance, reliability, and real-world constraints.
- Collaborate on infrastructure for model monitoring, validation, and continuous improvement.
- Translate complex analyses into clear insights for engineers, operators, and leadership.
- Frame solutions to ambiguous, open-ended problems to achieve buy-in from various stakeholders by focusing on the business impact of your projects
- Communicate uncertainty, tradeoffs, and model behavior effectively.
- Partner cross-functionally with software, data engineering, product, and event-reporting teams.
- Help shape technical direction and best practices for ML at Gridware. This includes exemplifying standards for experiment tracking, model versioning, reproducibility, and lifecycle management.
Production Engineering
Collaboration & Communication
Required Skills
- 5+ years of experience in machine learning, signal processing, or applied physics in production environments.
- Strong programming skills in Python and experience contributing to large, shared codebases.
- Experience working within modern software stacks, including cloud platforms, containerization, and CI/CD workflows
- Excellent written and verbal communication, especially explaining data and models clearly.
Bonus Skills
- Experience with Graph Neural Networks or learning over physical/topological systems.
- Familiarity with power systems, embedded sensing, or edge ML.
- Proven experience with time-series modeling and noisy real-world sensor data.
- Experience with multimodal learning or sensor fusion.
- Track record of technical leadership or mentoring.
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
Compensation (from employer):
190000–205000 USD per year
About this role
Summary
Develop algorithms and models for sensor data analysis, fault detection, and grid modeling in production.
Job title
Senior ML Engineer, Multi-Sensor Modeling
Experience level
5+ years
Minimum experience
5+ years exp
Industry
technology
Location requirements
San Francisco-based; remote work not specified
Salary
$190k–$205k
Management role
No
Skills & keywords
Required skills
Pythoncloud platformscontainerizationCI/CDcommunication
Preferred skills
graph neural networkspower systemssensor fusiontime-series modelingmentoring
Specializations
machine learningsensor datamultimodal learninggraph neural networksgeospatial modeling
Locations
Structured locations inferred from the posting.
San Francisco, CA, USA
Hybrid City
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