Simulation Platform Engineer

I’m partnering with a fast-growing climate/insurtech startup building advanced simulation and digital twin platforms to model real-world risk across environmental perils. Their technology combines physics-based simulation, machine learning, and geospatial data to power critical decision-making in areas such as wildfire, hurricane, and flood risk.

As they expand into new geographies and perils, they are hiring a Simulation Platform Engineer to own and scale the infrastructure and pipelines underpinning these modeling workflows.

This is a highly cross-functional role at the intersection of infrastructure, simulation, and data engineering, with end-to-end ownership of systems that directly impact core business outcomes.

This is a full time, 4 days per week onsite position in San Francisco.

Key Responsibilities:

• Own and maintain production simulation pipelines, including debugging, monitoring, and improving uptime and incident response across modeling workflows.
• Strengthen CI/CD processes and infrastructure reliability across simulation, digital twin, and ML pipelines through automated testing and efficient deployment strategies.
• Build and operate annotation and quality control systems for digital twins, leveraging ML-assisted workflows to improve data quality and reduce manual effort.
• Develop new digital twin capabilities, including features supporting additional perils such as wind and flood.
• Integrate new simulation pipelines end-to-end, connecting geospatial data, preprocessing, simulation workflows, and post-processing systems.
• Collaborate closely with machine learning engineers to support training, inference, and continuous improvement of AI-driven models.
• Design and operate scalable geospatial data pipelines, combining diverse datasets into reproducible, production-grade workflows.
• Communicate effectively across teams on system performance, data quality, and pipeline reliability to enable rapid iteration.

Key Qualifications:

• 5+ years of experience in backend or infrastructure engineering, with a focus on building production-grade data or simulation pipelines.
• Proven experience owning and operating complex, distributed, data-intensive systems end-to-end.
• Hands-on experience with cloud infrastructure, CI/CD pipelines, monitoring, and alerting systems.
• Experience working in fast-paced startup environments with high ownership.
• Background supporting physics-based or simulation-heavy workflows.
• Strong academic background in Computer Science, Engineering, Applied Mathematics, Physics, or a related field.
• High level of physics literacy to effectively work within simulation-driven environments.