Power Systems Research Scientist
Gridmatic
Company Overview
Gridmatic
Cupertino, CA, United States
2016
Approximately 50 employees and annual revenue estimated between $5 million and $10 million (source: cience.com, climatebase.org).
What They Do
Gridmatic is a private AI-enabled power marketing company that specializes in optimizing renewable energy and battery storage operations through advanced machine learning algorithms. Founded in 2016, the company focuses on forecasting energy supply, demand, pricing, and grid transactions in key U.S. markets such as ERCOT (Texas) and CAISO (California) (source: cience.com, gridmatic.com). Their core technology leverages AI and machine learning models to predict electricity market dynamics, which helps optimize operations for renewable energy generators, battery storage systems, and retail energy consumers. This innovative approach allows Gridmatic to differentiate itself from traditional power marketers that rely on manual processes (source: gridmatic.com, gridmatic.com). The company offers a range of products and services, including bid optimization for storage owners, revenue-sharing agreements, and retail energy contracts tailored for large energy users like data centers (source: gridmatic.com, gridmaticretail.com).
Projects & Track Record
Gridmatic has successfully managed several notable projects, including a 50 MW / 100 MWh battery storage system in Texas, which became operational in 2023 through its $50 million Energy Storage Fund (source: gridmatic.com). Another significant project is the 57 MW / 114 MWh Cross Trails Battery Energy Storage System (BESS) in Scurry County, Texas, which has a 10-year offtake agreement with Energy Vault, with construction expected to start following a recent announcement (source: ess-news.com). Additionally, Gridmatic is involved in the 100 MW / 400 MWh Caballero BESS in Nipomo, California, where it serves as the optimizer for Alpha Omega Power, and has signed a 10 MW solar Power Purchase Agreement (PPA) in ERCOT with Sol Systems to provide hourly-matched clean energy for EdgeConneX data centers (source: gridmatic.com). These projects highlight Gridmatic's commitment to expanding its footprint in the renewable energy sector.
Recent Developments
In the past two years, Gridmatic has made significant strides, including the closure of its $50 million Energy Storage Fund in November 2023, which enables the operation of the 50 MW Texas battery and aims to manage up to 500 MW in total (source: gridmatic.com). The company also signed a 10 MW ERCOT solar PPA with Sol Systems for EdgeConneX in 2024 and secured a 10-year offtake for Energy Vault's 57 MW Cross Trails BESS (source: gridmatic.com). Furthermore, Gridmatic partnered with Alpha Omega Power as the optimizer for their 100 MW Caballero BESS, which was announced in December 2024, thereby boosting its portfolio to 300 MW (source: ess-news.com). The company also launched Gridmatic Retail in October 2024, focusing on growth in Texas and expanding into PJM markets.
Working There
Gridmatic employs a diverse range of professionals, including researchers, engineers, data scientists, and energy veterans, all contributing to its innovative approach in the energy sector. The leadership team includes CEO & Founder Matt Wytock, Chief Commercial Officer David Miller, and CFO Erin Kogan, among others (source: gridmatic.com). The company culture emphasizes teamwork, continuous learning, diversity, and integrity, fostering a collaborative environment that values work-life balance. Hiring is primarily centered at its Cupertino headquarters, supporting growth in ERCOT, CAISO, and PJM markets (source: climatebase.org). While specific benefits are not publicly detailed, Gridmatic's status as a ClimateTech startup in the Bay Area suggests competitive perks aligned with its mission-driven ethos.
Last updated on Feb 23, 2026 | Report an issue
We are looking for a Power Systems Research Scientist to develop physics-based models of large-scale transmission systems and their impact on electricity markets.
You will work on large-scale optimization and simulation problems, including power flow, congestion, and security-constrained unit commitment and economic dispatch (SCUC/SCED). This role focuses on designing scalable algorithms and high-performance implementations for solving complex power system problems.
This role sits at the core of our research and trading stack, building models and computational tools that directly impact how we understand and operate in electricity markets.
We are particularly interested in rethinking power system optimization and simulation using modern computing (e.g., GPU acceleration).
What you'll do
- Develop and analyze power network models, including AC/DC power flow, contingency analysis, and security constraints
- Build and enhance large-scale optimization models (e.g., SCUC/SCED) with detailed transmission constraints
- Design and implement scalable algorithms and solver components for large-scale power system optimization
- Identify and address computational bottlenecks in network-constrained simulations and optimization
- Model and analyze congestion and transmission-driven market outcomes
- Simulate grid scenarios with high penetration of renewables, storage, and outages
- Collaborate with ML and trading teams to integrate network-aware signals into forecasting and decision systems
Qualifications
- Advanced degree (MS/PhD) in Electrical Engineering, Power Systems, or related field
- Strong background in power systems analysis and modeling
- Experience with power flow (AC/DC), transmission modeling, and congestion analysis
- Familiarity with ISO/RTO markets and network-constrained market outcomes
- Experience with optimization algorithms and large-scale mathematical programming
- Understanding of numerical methods for convex and/or non-convex optimization
- Strong programming skills in Python
Nice to Have
- Experience with tools such as PSS/E, PowerWorld, PSLF, or similar
- Familiarity with SCUC/SCED implementations
- Background in electricity market modeling or trading
- Experience working with large-scale datasets and cloud applications
- Familiarity with key power systems concepts such as PTDFs (power transfer distribution factors) and security constraints
- Experience with GPU-accelerated computing for large-scale optimization or simulation
- Experience with frameworks such as PyTorch or JAX for high-performance numerical computing
Taking care of you today
- Continuing Education Opportunities
- Flexible PTO
- Medical, Dental and Vision plans with competitive employer contributions
- Pre-Tax commuter benefits
- $1500/year non profit donation matching program through Millie
- Home Office Stipend
Protecting your future for you and your family
- 401K contribution match up to 4%
- Company-paid parental leave
- Company Paid Life Insurance
- Stock Option Loan Program
Pay range
$175,000 - $235,000 USD
Apply now
Job expired?Please let Gridmatic know you found this job on Rejobs. It helps us grow and get more people working in renewable energy.
Apply now
Job expired?Please let Gridmatic know you found this job on Rejobs. It helps us grow and get more people working in renewable energy.
See how you’re connected
View connectionsSee your contacts at Gridmatic on LinkedIn and tap your network when applying for this position.
Get job alerts
Get alerts for Energy Analytics jobs in Cupertino, United States
Join Talent Pool
Let clean energy employers find you
About the role
June 23, 2026
Full time
Company
- Cupertino, United States
Advanced degree with strong background in power systems analysis and modeling
UTC-08:00
