Relativity Spaceposted 15 days ago
Senior
Long Beach, CA
Transportation Equipment Manufacturing

About the position

We are seeking a Staff Software Engineer with broad technical skills and a hands-on mindset to support the development and deployment of a state-of-the-art process monitoring software integrated with advanced robotics, machine learning, and welding processes. This role is ideal for someone who thrives in cross-functional environments, enjoys owning full projects from design to deployment, and is comfortable navigating ambiguity in a fast-moving R&D setting. You'll contribute to the core software infrastructure that connects edge hardware, ML inference systems, real-time process monitoring tools, and visualization platforms.

Responsibilities

  • Design, implement, and maintain software systems that support process monitoring, anomaly detection, data collection, model inference, and operator interfaces
  • Own and deliver full-cycle software projects that span services, tooling, infrastructure glue, and edge interactions
  • Build APIs and system interfaces to connect data, ML, and robotics subsystems
  • Collaborate cross-functionally with robotics, machine learning, infrastructure, and data engineering teams
  • Troubleshoot and optimize systems running on edge Linux devices and local networks
  • Contribute to internal tooling that improves developer productivity and system observability

Requirements

  • 7+ years of professional software engineering experience
  • Strong proficiency in a Linux-based development environment, including CLI tools, shell scripting, and system debugging
  • Experience developing and shipping production-quality software with real-world operational constraints
  • Ability to independently scope, design, and execute technical projects
  • Comfortable working across domains and learning new technologies as needed

Nice-to-haves

  • Experience building software for or with hardware (e.g., instrumentation, industrial equipment, embedded systems)
  • Familiarity with data pipelines, ML model serving, or telemetry collection
  • Exposure to edge computing environments and networked systems
  • Prior experience in a small company or startup where you owned software end-to-end
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