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Tapestry
Mountain View, California, United States • Hybrid
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You will architect and lead the technical roadmap for Tapestry's machine learning systems to optimize continental-scale power grids. This involves collaborating with cross-functional teams to translate complex grid data into actionable insights and mentoring senior engineering staff.
Candidates must have a Master's or PhD in a quantitative field and over 10 years of experience building large-scale production machine learning systems. Additionally, 4+ years of professional experience in grid modeling, simulation, or power-system optimization is required.
Tapestry is a team within Alphabet working to build the AI-powered electric grid. We are tackling one of the world’s most important infrastructure challenges: helping the energy system become more visible, understandable, reliable, affordable, abundant, and clean.
Originally born at X, Alphabet’s moonshot factory, Tapestry brings together experts in energy, AI, software, engineering, and product to build tools that help the electricity ecosystem plan smarter, move faster, and operate more efficiently.
This is a global effort. Tapestry supports partners across the U.S., U.K., Chile, New Zealand, Australia, and Brazil as they work toward a cleaner, more resilient energy future.
Joining Tapestry means doing high-impact work with a multidisciplinary team tackling a problem that matters at global scale. Learn more about our team and our mission here.
You will serve as a foundational architect of Tapestry’s multi-year machine learning strategy, bridging cutting-edge AI research, the physics of continental-scale power grids, and the development of production ML/AI systems. You will architect machine learning systems that advance grid planning, simulation, and asset intelligence at continental scale.
A culture that supports growth, ownership, and meaningful impact, along with…
The US base salary range for this full-time position is $262,000 - $361,000 + bonus + equity + benefits. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits.
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