Exowatt is revolutionizing the energy landscape for the AI era with our groundbreaking P3 system that captures solar energy, stores it as heat, and generates electricity on demand. Founded in 2023 and backed by leading investors including Andreessen Horowitz, Sam Altman, and Felicis, we're committed to providing clean, modular, and scalable power that meets the rapidly growing demands of AI infrastructure. Our mission is to make sustainable renewable energy always available and almost free, enabling technological advancement while protecting our planet.
We are seeking an innovative Lead Software Engineer to pioneer the application of Large Language Models (LLMs) and AI to solve complex physics and engineering challenges in our renewable energy systems. This unique role combines cutting-edge AI technology with fundamental physics to optimize thermal dynamics, predict system behavior, and accelerate our engineering development cycles.
You will lead the development of AI-powered tools that help our engineers design better systems, predict performance under various conditions, and solve multiphysics problems that are critical to our generation, thermal energy storage and conversion technology. This is a rare opportunity to apply the latest advances in AI to real-world energy challenges that will power the future of computing.
This position is based in Miami, FL. If selected, relocation to Miami, FL is required. Exowatt provides relocation assistance.
Key Responsibilities
Develop AI/LLM-based models for complex thermodynamics, heat transfer, and fluid dynamics.
Implement AI to interpret, validate, and optimize physics simulations.
Ensure AI solutions adhere to thermodynamics principles.
Stay updated on advances in AI/physics-informed computing.
Collaborate externally and represent Exowatt in scientific forums.
Integrate AI frameworks with engineering simulation platforms (e.g., ANSYS).
Build scalable, cloud-based software architectures and real-time data pipelines.
Lead AI-driven digital twin and predictive analytics for system optimization and maintenance.
Required Qualifications
Bachelor's degree in Computer Science, Physics, Engineering, or related field; Master's or PhD preferred
7+ years of software engineering experience with at least 3 years focused on AI/ML applications
Track record of building production AI systems that solve real-world problems
Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow, JAX)
Strong proficiency with LLM frameworks and tools (Hugging Face, LangChain, OpenAI API, Anthropic Claude)
Solid understanding of physics fundamentals, particularly thermodynamics and heat transfer
Proficiency with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes)
Experience with MLOps practices and model deployment pipelines
Preferred Qualifications
Expertise in physics-informed neural networks (PINNs) or neural operators
Domain experience with renewable energy, thermal systems, or concentrated-solar-power (CSP)
PhD in Computational Physics, Applied Mathematics, or AI/ML (physics-focused)
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