Robotics Software Engineer III - Infrastructure - Vaux at ArcBest in Boston, Massachusetts, United States

Job description

• Company
• ArcBest
• Location
• Nationwide Availability
• Workspace
• On-Campus
• Pay Type
• Salary, Full-Time
• Job ID
• 29646
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• 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.

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 pipelines for deploying software and models to development vehicles, test fleets, and production systems.
• Enable vehicle-level observability through logging, metrics, and distributed tracing.
• Support rapid diagnosis of field issues and feedback loops into development, testing, and simulation environments.
• Enable traceability for safety-critical systems, including the ability to identify what software, model, and configuration ran on a specific vehicle at a given time.
• Support functional safety requirements by enabling reproducible builds, preserving validation evidence, and supporting audits and certification activities (e.g., ISO 3691-4, ISO 13849).
• Collaborate closely with Functional Safety Engineering to ensure infrastructure aligns with compliance and certification needs.
• Act as a force multiplier for autonomy engineers by reducing duplicated tooling and infrastructure maintenance overhead.
• Make pragmatic trade-offs between development velocity, system reliability, and safety requirements.
• Mentor engineers on platform usage, infrastructure best practices, and scalable system design.
• Influence technical direction across teams without direct people management responsibility.
• Other duties and projects, as assigned.

Requirements

• Bachelor's Degree in Computer Science, Robotics, Electrical Engineering, Mechanical Engineering, or related field, required
• Master's Degree or equivalent industry experience in robotics, autonomous systems, or distributed systems, preferred
• 4 years of experience in software infrastructure, platform engineering, or DevOps position(s), preferred
• Hands-on experience with Linux-based systems and containerized environments, required
• Experience working with CI/CD systems, build tooling, and artifact management solutions, required
• Familiar with Bitbucket and Jira automation, preferred
• Practical experience with MLOps, including dataset and model versioning and deployment pipelines, preferred
• Familiar with robotics middleware such as ROS or ROS2, preferred
• Experience supporting complex, distributed, real-time, or hardware-integrated systems, required
• Proven ability to design and maintain systems used by multiple teams and products, preferred
• Exposure to simulation-heavy environments or systems that integrate tightly with physical hardware.
• Experience in robotics, autonomous systems, or embedded software development, preferred
• Experience with SIL and HIL testing methodologies, preferred
• Experience working in safety-critical or regulated environments, preferred
• Understanding of vehicle systems, sensors, and real-world deployment constraints, preferred

Skills

Required

• Linux-based systems
• Containerized environments
• CI/CD systems
• Build tooling
• Artifact management solutions

Preferred

• Bitbucket
• Jira automation
• MLOps
• Dataset and model versioning
• Deployment pipelines
• ROS or ROS2
• SIL and HIL testing