Power Systems Engineer

Job Description Summary

In pursuit of accelerating the energy transition and recognizing the grid's significance in this transformation, Thinklabs AI is an AI-focused technology company building next-generation software for electric power system simulation, optimization, and analytics. Our focus is to modernize power systems analysis by combining rigorous power systems engineering, advanced numerical methods, optimization, high-performance computing, and modern AI/ML techniques. As grid models and analytical workloads grow in size and complexity, computational performance has become central to enabling faster studies, broader scenario analysis, and more scalable decision-making.

We are seeking a skilled Power Systems Engineer to lead the design and development of advanced power systems technologies and the high-performance computing foundation that runs them. You will design production-quality software in modern C++, with GPU acceleration (CUDA) as a first-class design goal. Operating within a mission-driven, disruptive innovation, agile, and fast-paced culture, you will actively participate in highly complex global projects and innovative customer engagements. As a vital member of the R&D team, you will play a crucial role in algorithm research, hands-on implementation, and performance engineering.

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Job Description

This role combines deep power system domain expertise, mathematical and numerical rigor, and high-performance software engineering. The ideal candidate understands the underlying mathematics and physics of power systems, and is equally comfortable turning that understanding into fast, numerically robust native code that exploits modern CPU and GPU hardware.

You will work closely with power systems specialists, numerical engineers, and AI engineers to translate computationally intensive algorithms into scalable production software, and to rethink how traditional power system analysis can evolve using modern software, HPC, and AI approaches.

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Responsibilities

Power System Algorithms

• Design and implement transmission/distribution robust and scalable algorithms from the ground up.
• Ensure numerical correctness, consistency, and reproducibility of results across CPU and GPU implementations.
• Investigate advanced power system methods and evaluate and integrate open-source numerical and optimization libraries.

High-Performance C++ and GPU Implementation

• Develop production-quality scientific computing software in modern C++ with a strong emphasis on performance, memory efficiency, and maintainability.
• Lead the architecture and evolution of GPU-accelerated compute capabilities across the simulation and optimization platform.
• Design and optimize numerical workloads for modern GPU hardware, including memory management, workload batching, data movement, and asynchronous execution.
• Profile complex computational workloads, identify bottlenecks, and drive measurable performance improvements; help evolve the platform toward larger workloads and multi-GPU execution where appropriate.
• Improve data movement and integration between high-performance native code and application-level (e.g., Python and service) components.
• Contribute to reliable build, testing, deployment, and performance-validation infrastructure for native and GPU-enabled software.

AI-Enabled Computation

• Develop ML-assisted initialization and warm-start approaches for power systems applications; explore AI-assisted contingency screening and ranking.
• Build interfaces between optimization engines and AI workflows; investigate surrogate models and physics-informed ML methods.
• Research how AI and GPU computing together can accelerate or improve traditional power system computations, and use AI-assisted coding workflows to increase development productivity.

Architecture and Technical Leadership

• Architect extensible software infrastructure and APIs, and contribute to scalable computational frameworks for transmission-system studies.
• Serve as a deep technical expert in power system mathematics, technologies, and performance engineering; help define the long-term technical direction of the platform.
• Establish engineering practices for performance benchmarking, numerical validation, code quality, and GPU software development.
• Mentor engineers and researchers across power systems, HPC, and AI domains; bridge communication between AI engineers, software engineers, and power system specialists.

Basic Qualifications

• Master's degree in electrical engineering, applied mathematics, physics, computer science, or a related technical field, with a minimum of 3 years of relevant working experience.
• Deep understanding and a strong background in transmission and/or distribution system analysis and modeling. Familiarity with industry simulation tools such as PSS/E, PSLF, DSATools, OpenDSS, or ETAP.
• Strong professional experience developing high-performance or computational software in modern C++ (C++17 or later), including maintainable, tested, production-quality systems software.
• Hands-on experience with GPU programming and CUDA, including developing, profiling, and optimizing numerical workloads, and a solid understanding of GPU architecture, parallel computing, memory management, and asynchronous execution.
• Strong mathematical foundation in linear algebra, sparse matrix methods, and numerical methods, with a clear understanding of numerical accuracy, floating-point behavior, and reproducibility in scientific software.
• Experience implementing algorithms directly rather than only using commercial tools, and the ability to move fluidly between research ideas and working implementations.
• Demonstrated ability to use profiling and benchmarking to identify bottlenecks and deliver measurable performance improvements.
• Working proficiency in Python and familiarity with Linux, Docker containers, modern build/test/deployment practices, and microservice environments.
• Experience applying AI/ML to physical systems or optimization problems; familiarity with machine learning and large language model (LLM) tooling.
• Strong analytical, problem-solving, communication, and technical leadership skills, and the ability to collaborate effectively across engineering and domain-specialist teams in a remote environment.

Desired Characteristics

The ideal candidate enjoys going deep into power systems internals, understands the mathematics “under the hood,” likes building things from first principles, can transition from whiteboard mathematics to production C++ and CUDA code, and is excited about using GPU computing and AI to rethink traditional power system analysis workflows.

• Ph.D. in electrical engineering, applied mathematics, physics, computer science, or a related technical field, with a minimum of 5 years of relevant working experience.
• GPU-accelerated sparse direct power systems technologies; sparse matrix factorization and large-scale sparse linear system solving.
• GPU acceleration of optimization or scientific-computing workloads; multi-GPU or distributed high-performance computing; other NVIDIA numerical libraries (cuSPARSE, cuBLAS, cuSOLVER) and GPU computing frameworks.
• Proven experience as a power systems engineer with expert knowledge of power system models, model validation and calibration, and steady-state, transient, and dynamic analysis.
• Experience shipping production scientific, engineering, simulation, or optimization software.
• Industry reputation, prior IEEE/CIGRE publications on practical power systems engineering topics, and participation in industry standards, working groups, or task forces.

Personal Attributes

• Challenges conventional thinking and traditional ways of operating with conviction and vision; actively encourages stakeholders to identify issues and opportunities. Balances an understanding of present realities with a collaborative drive towards shaping the future.
• Adopts a holistic systems perspective, envisioning, comparing, and contrasting multiple potential long-range futures. Demonstrates empathy towards multiple points of view.
• Possesses a genuine passion for the customer and a strong conviction in addressing problems worth solving.
• Embraces a desire for personal and professional growth, fostering innovation, creativity, curiosity, and a collaborative mindset.

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What Success Looks Like

In this role, you will make increasingly large and complex transmission-system studies practical to run in production. You will deliver robust power systems applications, establish scalable C++ and GPU computing patterns, improve performance across critical workloads, and help build a high-performance engineering foundation that evolves with the needs of the platform. You will also serve as a technical leader who helps the broader team make sound architectural decisions and develop reliable, efficient numerical software at scale.