Power System Applications Engineer at Gridmatic

Cupertino, California, United States

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Not SpecifiedCompensation

Mid-level (3 to 4 years), Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Electric Power, Clean EnergyIndustries

Requirements

Master’s degree in Electrical Engineering or Power Systems Engineering with a minimum of 4 years of experience in the electric power industry or a Ph.D. in Electrical Engineering or Power Systems Engineering with coursework in power network applications
Experience with collaborative software development in Python and/or other languages
Knowledge of optimization techniques (e.g., convex optimization, stochastic optimization, robust optimization, etc.)
Knowledge of performing power systems network modeling using network topological analysis, power flow, contingency analysis, state estimator, security-constrained unit commitment, and economic dispatch
Experience with two or more power system simulation tools (e.g., PSS/E, Powerworld, PSLF, or similar)
Familiarity with Security Constrained Unit Commitment (SCUC) and Security Constrained Economic Dispatch (SCED) combined with a background in power system dynamics and stability
Familiarity with modeling renewables, energy storage, and independent system operator (ISO) electricity markets

Responsibilities

Simulate and develop models and tools to analyze the electricity energy market, including simulating ancillaries and transmission constraints
Contribute to the development of power market analysis tools delivering innovative solutions in the areas of network modeling, network analysis, power flow, security/contingency analysis, and real-time control
Perform an advanced quantitative and economic analysis of energy markets to assess the future of the electric power market and prices, power plant operation and valuation, environmental emissions and compliance, transmission, and regulatory effects, among other parameters
Stay abreast of market developments and provide fundamental analysis, insights, and perspectives on electricity markets

Skills

SCUC

SCED

Power Flow

Network Modeling

Contingency Analysis

Security Analysis

Power System Dynamics

MIP

Linear Programming

Convex Programming

Stochastic Optimization

Gridmatic

AI-driven optimization for renewable energy assets

About Gridmatic

Gridmatic uses artificial intelligence to improve the performance and profitability of renewable energy assets. It serves renewable energy generators by predicting energy prices and managing risks, while helping storage operators optimize revenue and minimize non-performance risks. For consumers, Gridmatic aims to lower energy costs and support renewable energy procurement. The company stands out by combining advanced algorithms with market expertise to modernize energy markets and contribute to decarbonization.

Cupertino, CaliforniaHeadquarters

2020Year Founded

$5.8MTotal Funding

EARLY_VCCompany Stage

Energy, AI & Machine LearningIndustries

11-50Employees

Benefits

Hybrid Work Options

Flexible Work Hours

Risks

Increased competition from AI-driven energy optimization companies may erode market share.

Regulatory changes in Texas could impact operations as a Retail Electric Provider.

Cybersecurity threats to AI systems pose risks to data integrity and reliability.

Differentiation

Gridmatic uses AI to optimize renewable energy asset performance and profitability.

The company offers tolling, offtake, and supply contracts for clean energy assets.

Gridmatic is a licensed Retail Electric Provider in Texas, enhancing market credibility.

Upsides

Increased interest in AI-driven energy solutions boosts partnerships with energy providers.

The Inflation Reduction Act offers tax incentives, enhancing Gridmatic's financial attractiveness.

Advancements in battery technology improve storage efficiency, aligning with Gridmatic's focus.

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