Senior Software Engineer, Simulation

Location

El Segundo, CA

Full time

On-site

Engineering Software Engineering

• Annual Salary Range $158,000 – $219,450
  • Offers Equity

Radiant is an El Segundo, CA-based startup building the world’s first mass-produced, portable nuclear microreactors. The company’s first reactor, Kaleidos, is a 1-megawatt, fail-safe microreactor that can be transported anywhere power is needed and run for up to 5 years without refueling. Portable nuclear power with rapid-deploy capability can replace similar-sized diesel generators and provide critical asset support for hospitals, data centers, remote sites, and military bases.

Radiant’s unique, practical approach to nuclear development leverages modern software engineering to rapidly deliver safe, factory-built microreactors that use existing, well-qualified materials. Founded in 2020, Radiant is on track to test its first reactor at the Idaho National Laboratory this summer, with initial customer deliveries beginning in 2028.

Radiant is seeking an experienced Senior Software Engineer to design and implement robust software systems that power our reactor simulation and Digital Twin capabilities. In this role, you will serve as a key technical contributor on a high-performing team, owning the architecture, tooling, and infrastructure—including evaluation and integration of frameworks, third-party software, and simulation tools—that enables our simulation engineers to model, test, and validate reactor systems—accelerating our path to commercialization.

• Implement and contribute to software architecture for simulation systems across thermal, hydraulic, and nuclear reactor multi-physics models.

• Collaborate with and support simulation engineers developing reactor and subsystem physics models.

• Build and maintain software infrastructure to support Digital Twin simulation, visualization, and data processing capabilities.

• Contribute to the technical roadmap for thermal and safety analysis simulation. Develop and execute strategies for model tuning as models and frameworks evolve.

• Drive technical excellence by following and reinforcing best practices for simulation software development, code quality, and testing standards.

• Evaluate and recommend third-party software tools, open source libraries, and simulation frameworks for adoption by the team.

• Collaborate cross-functionally with Hardware, Nuclear, and Electrical engineering teams to accelerate software-in-the-loop and hardware-in-the-loop testing capabilities.

• Contribute to the delivery of mission-critical internal simulation products while ensuring sustainable development practices and technical debt management.

• Support team growth through knowledge sharing and contributing to a high-performance engineering culture.

• Bachelor's degree in physics, mechanical engineering, computer science, or a similar field.

• 5+ years of professional software engineering experience with significant depth in high performance computing (HPC), computational science, Machine Learning, or a related advanced computing field.

• Expert-level proficiency in programming languages such as Python, Rust, or C/C++.

• Strong background in 3rd party simulation tools, physics-based modeling, numerical methods, or computational science with proven ability to execute technical strategy.

• Proficiency with visualization frameworks, open source platforms, and automated testing approaches for scientific software.

• Strong foundation in software engineering best practices, including version control, code review, and CI/CD pipelines.

• Proven ability to deliver high-quality hands‑on technical contributions within a collaborative team environment.

• Advanced degree (Master's or Ph.D.) in physics, computer science, mechanical engineering, or a similar field.

• Experience contributing to simulation or computational modeling, parallel computing, or high-performance computing projects.

• Background with modern simulation frameworks, finite element analysis, or computational fluid dynamics tools.

• Experience with Machine Learning, Deep Learning, or other…