Computational Physics Software Engineer

Overview

Are you interested in the intersection of differentiable programming, software engineering, and computer science? Are you interested in developing innovative solutions to enable the next generation of Autonomous Systems? Passive Logic is looking for a highly motivated and dedicated candidate who wants to learn from the best and stretch their skills.

Passive Logic is the first fully autonomous platform for buildings. We’ve reinvented the fundamental principles of automation to democratize technology, optimize buildings, and reduce the world’s carbon footprint. We are a team of technologists, engineers, and creatives dedicated to making a sustainable impact through real-world solutions.

We are looking for team members who have a passion for technology and want to work on cutting-edge problems with real-world solutions. Our culture is built on bringing together the most talented engineers, thinkers, and creatives—backed by the world’s leading investors—working together to make the future a reality.

This is a career-defining opportunity to play a crucial role in a hyper-scale AI company that is transforming the future of autonomous systems, energy, and the built environment.

As the Computational Physics Software Engineer, you will play a meaningful role in our AI team developing differentiable physics-based equipment inferencer environment within an AI-driven control engine.

• Build infrastructure: Develop and maintain infrastructure for a differentiable multi-physics simulation engine.
• Design interfaces: Develop an interface with the object model through Object Relational Mapping.
• Control path support: Provide an infrastructure to support Passive Logic’s control path predictor and front-end simulation environments.
• Develop autonomous systems: Develop robust autonomous software that must run with no human supervision for decades.
• Ensure robust systems: Use thoughtful architecture design, documentation, unit testing, integration testing, profiling, and collaboration with the Formal Methods team to ensure this robustness.
• Collaboration: Collaborate with the Digital Twins team for physics optimization and collaborate with the Compiler team for accelerator approaches.

If your experience does not meet all our posted requirements below, we’d still love to hear from you. We are looking for practitioners who are passionate about understanding people, committed to lifelong learning, and driven by the love of what they do. If that’s you, please apply!

• Proven experience: Strong proficiency in systems programming languages such as Swift, Rust, C++, or Java, as well as appreciable software engineering skills in working with large codebases with non-trivial architecture, beyond just coding small (1000’s of lines) programs and scripts
• Exceptional communication skills: Extraordinary teammate with excellent interpersonal skills.
• Organized and strategic: Experience with software design, design patterns, and software architecture
• Collaborative mindset: Strong self-motivation towards Passive Logic’s mission to “empower people through generative autonomy to solve the world's largest climate challenges.”
• Adaptability: Comfortable in a fast-paced startup environment, eager to learn, iterate, and innovate.
• Problem solving: You own this role. When issues arise, be the empowered force that solves them, rolling-up.

• Experience with: Code performance and memory optimization
• Concurrency, threads, processes, Lib-dispatch/GCD
• GPU programming, high-performance computing, and scientific computing
• Vector, SIMD, and tensor computational methods
• Strong math, numerical methods, and analysis skills

• A relevant educational background: A BS, MS, or PhD in software engineering, computer science, applied mathematics, physics or other engineering degrees.
• Varied programming and domain experience: Experience with Swift programming language, auto-differentiation, systems modeling and algorithm development, fundamentals of building energy or electromechanical systems, and/or autonomous systems.
• Familiarity with the startup environment: Experience…