Simulation Engineer
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- Digital Twin Development: Architect and build high-fidelity, physics-based simulations of data center components, including cooling systems, power distribution units, and server racks.
- Simulation Platform Integration: Integrate individual asset models into a comprehensive, scalable simulation platform that represents entire data center environments.
- Model Validation: Develop methodologies to validate simulation accuracy against real-world operational data, ensuring our digital twins faithfully represent physical reality.
- AI Training Environments: Create and maintain the infrastructure and APIs that allow Reinforcement Learning engineers to train and evaluate control agents at scale within the simulation.
- Performance Optimization: Ensure the simulation platform is fast, scalable, and efficient to accelerate the AI/ML development lifecycle.
- Digital Twin Experience: 3+ years of professional experience in developing digital twins or high-fidelity simulations for complex physical systems (e.g., in energy, aerospace, manufacturing, or robotics).
- Strong Programming Skills: Proficiency in Python, Go and/or C++ and experience with simulation frameworks or libraries.
- Physics-Based Modeling: Strong understanding of first-principles modeling, with experience capturing the dynamics of physical systems (thermal, electrical, or mechanical).
- ML/AI Exposure: Familiarity with the lifecycle of machine learning models and experience creating environments for training and testing AI agents.
- Educational Background: MS or PhD in a relevant engineering discipline, Computer Science, Math or Physics.
- Problem Solver: A practical mindset, able to abstract complex physical interactions into computationally efficient models and troubleshoot discrepancies between simulation and reality.
- Competitive salary, bonus, 401(k) plan and equity in a rapidly growing startup
- Comprehensive health, dental, and vision coverage
- Opportunity to apply the latest AI technologies working with an experienced team
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