Robotics Software Engineer III - Infrastructure - Vaux

About the role

The Robotics Software Engineer III - Infrastructure is responsible for designing and enabling the foundational infrastructure that supports the full lifecycle of autonomous robotic systems, from source code to deployment and field observability. This position provides high leverage across perception, planning, controls, simulation, and safety teams by delivering durable platforms, shared workflows, and guardrails that allow product teams to move quickly without compromising reliability, traceability, or compliance. The Robotics Software Engineer III - Infrastructure sits at the intersection of robotics software, DevOps, simulation, and MLOps. This position focuses on building scalable systems and standards rather than acting as a first responder for day-to-day operational issues. Success is measured by reduced friction for autonomy engineers, improved release confidence, and infrastructure becoming a competitive advantage rather than a bottleneck.

About Us: ArcBest® (Nasdaq: ARCB) is a multibillion-dollar integrated logistics company that helps keep the global supply chain moving. Founded in 1923 and now with 14,000 employees across 250 campuses and service centers, the company is a logistics powerhouse, using its technology, expertise and scale to connect shippers with the solutions they need — from ground, air and ocean transportation to fully managed supply chains. ArcBest has a long history of innovation that is enriched by deep customer relationships. With a commitment to helping customers navigate supply chain challenges now and in the future, the company continues to invest in purpose-built technology such as ArcBest View™, its digital logistics platform that brings quoting, booking, shipment visibility and reporting into one connected experience.

Responsibilities

• Design and enable shared infrastructure supporting the end-to-end robotics software lifecycle: Source, Build, Test, Simulate, Deploy, Monitor.
• Standardize build systems and CI/CD pipelines across robotics software, embedded systems, and simulation environments.
• Define and manage artifact versioning strategies for software binaries, firmware, configuration, calibration data, maps, and vehicle-specific parameters.
• Establish platform standards, reference architectures, and best practices used across multiple product teams.
• Enable large-scale Software-in-the-Loop (SIL), Hardware-in-the-Loop (HIL), and regression simulation workflows.
• Integrate simulation results into CI pipelines with clear pass/fail criteria and reporting.
• Support scenario-based testing, coverage tracking, and regression analysis.
• Provide infrastructure and tooling to improve correlation between simulation results and real-world vehicle behavior in collaboration with simulation and vehicle integration teams.
• Design and evolve shared infrastructure supporting the lifecycle of machine learning models used in autonomy systems.
• Enable dataset versioning, lineage tracking, training reproducibility, and model promotion workflows.
• Define standards for model packaging, deployment to vehicles, runtime monitoring, and rollback mechanisms.
• Partner with perception and autonomy teams to enable safe and performant model deployment, while domain teams retain ownership of model design and performance outcomes.
• Build and maintain reliable