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Mainspring Energy manufactures fuel-flexible, low-emissions local power solutions, including Linear Generators for Fortune 500 companies, data centers, and utilities. The company partners with major energy leaders including AEP, NextEra Energy Resources, and Schneider Electric.
You will own the performance characterization and validation of Mainspring's Linear Generator product. Reporting to the VP of Test Engineering, you will combine hands-on experimental work with rigorous data analysis to measure, understand, and improve all aspects of the generator's performance—power output, efficiency, and emissions profiles. Your central mission is ensuring products meet internal Product Requirements Document (PRD) targets and providing engineering teams with actionable insights to close performance gaps.
Key responsibilities include:
- Own measurement and tracking of product performance (power, efficiency, emissions) against PRD targets
- Identify performance gaps and drive cross-functional efforts to resolve them
- Design and execute experiments on Linear Generator test units, working hands-on with technicians and the test team
- Build and maintain Python-based analysis tools and pipelines to process large test datasets, quantify performance, and identify trends and root causes
- Apply first-principles thermodynamic and heat release analysis to explain observed performance
- Communicate results clearly to design engineering teams and make data-driven recommendations guiding design decisions
- Develop and improve test methods, instrumentation, and processes for next-generation product validation
This role is ideal for an engineer or researcher with deep expertise in thermodynamics and power generation who wants to apply it to a first-of-its-kind product in a fast-paced development environment.
REQUIREMENTS:
- PhD in mechanical engineering, aerospace engineering, chemical engineering, physics, or related field; OR Master's degree with several years of applicable industry or research experience
- Deep expertise in thermodynamics/power generation with ability to apply it to real hardware and experimental data
- Excellent data analysis skills in Python (pandas, NumPy, SciPy), including working with large, noisy experimental datasets
- Hands-on experience designing and executing experiments involving instrumentation and emissions testing
- Strong communicator with collaborative mindset, comfortable presenting findings to leadership and working across teams
- Strong organizational skills and ability to manage multiple priorities against deadlines
