Senior Computational Scientist, Electric Grid Simulations

We are seeking a talented grid simulations and computational specialist to join Tapestry and help expand our high-performance grid computation capabilities. In this role, you will bridge power system physics with modern software architecture, designing simulation algorithms and optimization tools capable of handling complex, large-scale electrical networks.

You will collaborate closely with a multidisciplinary team of AI researchers, software engineers, power systems domain experts, and product managers to turn complex technical challenges into production-ready solutions. By building advanced computational capabilities, you will empower global energy partners to accelerate the transition to clean energy, improve grid reliability, and unlock transformative 10x impact across the global energy ecosystem.

Tapestry is a group within Google 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 products 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.

• Work with power system and software engineering experts on the design and creation of advanced simulation and optimization tools.
• Develop codes and algorithms to take full advantage of powerful, modern computer hardware.

What you should have

• Master or PhD in Electrical Engineering.
• Solid expertise and a deep understanding of core power systems and power electronics principles.
• 6+ years of experience in power systems or power electronics modeling and simulations.
• Experience in one or more general-purpose programming languages such as Python, Java, or C/C++.
• Understanding of numerical methods, including solving nonlinear/linear differential equations, differentiation and integration, and time discretization.

It’d be great if you had these

• Experience conducting power system planning and interconnection studies.
• Are a skilled and efficient programmer in scientific programming languages (e.g, JAX, C++, Julia, etc.) with a desire to expand into new areas of coding languages and processes.
• Familiar with Machine Learning concepts.

• Competitive salary and equity
• Medical, dental, and vision coverage
• Generous PTO and flexible hybrid work model
• 401(k) with employer contribution
• Professional development
• The ability to work on important real-world problems within an Alphabet-backed environment

The US base salary range for this full-time position is $174,000 - $261,000 + 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.

• Take charge: We take initiative and own outcomes that move the mission forward.
• Transform with purpose: We build solutions that solve real problems and create meaningful impact.
• Be a Tapestry, not a thread: We collaborate across diverse skills and perspectives to achieve more than we can individually.
• Always fine-tune: We stay curious, seek feedback, and refine our understanding as we learn.
• Stay grounded: We listen openly, value different perspectives, and stay focused on what matters most.