PhysicsX

Senior Software Engineer focused on designing, operating, and scaling PhysicsX’s core infrastructure across multi-cloud, on-premises, and Kubernetes environments. The role combines platform reliability, infrastructure automation, multi-tenancy, secrets management, networking, and accelerated compute.

Build and operate production-scale AWS infrastructure, CI/CD pipelines, and self-service platform tooling for an AI-driven simulation company. This hands-on DevOps role offers significant influence in a hybrid scale-up environment.

Lead the design and implementation of secure development practices as a Principal Security Engineer, integrating security into engineering workflows and CI/CD pipelines. This high-impact role combines DevSecOps, application security, threat modeling, vulnerability management, and security architecture.

Staff Backend Software Engineer building distributed systems and platform services for high-fidelity AI-driven simulation and machine learning workflows. The role combines hands-on Go and Python development, ML platform engineering, architecture, cross-team ownership, and technical mentorship across cloud and air-gapped environments.

Lead the delivery of scalable machine-learning systems that turn advanced engineering and physics models into practical customer solutions. This customer-facing technical leadership role combines ML engineering, deployment, architecture, and mentoring across global delivery projects.

Build and deploy customer-facing software that applies PhysicsX’s physics AI models to complex engineering and manufacturing challenges. You’ll work directly with customers and cross-functional technical teams, with regular travel to customer sites worldwide.

Build scalable physical foundation models and production-quality machine-learning systems for high-impact engineering and manufacturing problems. You’ll translate research into robust software while collaborating with scientists, engineers, customers, and partners.

Build and deliver scalable machine learning systems that embed AI models into real-world engineering and manufacturing workflows. This customer-facing role combines ML engineering, 3D geometry data, cloud infrastructure, and practical deployment impact.