Power Systems Research Scientist

🏢 Gridmaticinc · 📍 Cupertino 💰 $175,000 - $175,000 / yr

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Position Summary & Responsibilities

The Role

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
Backgro

🎯 Candidate Preparation Guide For Gridmaticinc Applicants

Key Role Competencies & Evaluation Highlights

Key Role Focus:

Evaluating your ability to handle complex optimization problems, real-time energy markets, and data-driven decision making under uncertainty.

📋 Preparation Priorities (Key Areas to Clarify):

1. Treating power markets like standard SaaS software with zero regard for physical asset constraints.
2. Overcomplicating basic system architectures without focusing on execution speed.
3. Lack of domain curiosity regarding renewable energy integration or battery storage.

✨ Recommended Role Alignment Hook:

I build resilient machine learning and optimization systems that turn volatile energy markets into predictable, high-margin assets.

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