Autonomous Robotics Launch Manager

Ford Ford · Auto · Dearborn, MI +1 · PD Operations and Quality

Lead a multi-plant engineering team to define, develop, and deploy next-generation autonomous robotics technologies for Ford's manufacturing logistics. This role oversees AMR/AGV platforms, embedded controls, ML-based perception, ADAS-inspired autonomy, and large-scale software integrations. Responsibilities include technical leadership for autonomy software, sensor fusion, perception, mapping, localization, motion planning, and safety systems, as well as software-driven project execution and multi-plant launch leadership. The role also involves embedded controls and hardware integration, and software validation using simulation environments.

What you'd actually do

  1. Lead a high-performing team of robotics engineers, software developers, and launch professionals delivering AMR/automation across multiple Ford manufacturing sites.
  2. Provide high-level technical oversight of autonomy software, ADAS-style sensor fusion pipelines, software frameworks, and computer vision integrations.
  3. Shape Ford’s long-term strategy for AMR autonomy stacks- including sensor fusion, perception, mapping, localization, motion planning, and safety systems.
  4. Lead authoring and negotiation of software-focused SOWs covering autonomy behaviors, fleet algorithms, sensor calibration requirements, MCU/SoC/MPU integration, and cybersecurity standards.
  5. Lead all software and controls readiness activities for AMR deployments during vehicle launches.

Skills

Required

  • Robotics engineering leadership
  • Software development leadership
  • AMR/automation deployment
  • Autonomy software oversight
  • ADAS-style algorithm understanding
  • Robotics controls expertise
  • Sensor fusion expertise
  • SOW creation
  • Vendor management
  • Full lifecycle robotics deployment
  • Embedded controls integration
  • Hardware integration
  • Software validation
  • Simulation environments (Gazebo, Isaac Sim, ROS)
  • Digital twin development
  • Automated test harnesses
  • Model-based design artifacts
  • Software validation reports

Nice to have

  • Master’s degree in Robotics, Software Engineering, Business Administration (MBA), or Technical Leadership
  • Architecting advanced robotics autonomy stacks
  • Architecting ADAS systems
  • Ford GVOSS
  • GME-707
  • Safety standards
  • Cybersecurity requirements
  • Virtual commissioning
  • PLC safety systems
  • Industrial networking

What the JD emphasized

  • ML-based perception systems
  • ADAS-inspired autonomy stacks
  • autonomy software
  • ADAS-style sensor fusion pipelines
  • autonomy stacks
  • sensor fusion
  • perception
  • mapping
  • localization
  • motion planning
  • safety systems
  • autonomy behaviors
  • fleet algorithms
  • perception models
  • localization maps
  • autonomy parameters
  • fleet software integration
  • routing algorithms
  • traffic orchestration
  • perception stack failures

Other signals

  • autonomous robotics technologies
  • ML-based perception systems
  • ADAS-inspired autonomy stacks
  • large-scale software integrations
  • perception modeling
  • mapping/localization
  • fleet management coding
  • autonomy stack refinement
  • sensor fusion
  • perception
  • mapping
  • localization
  • motion planning
  • safety systems
  • autonomy behaviors
  • fleet algorithms
  • perception models
  • localization maps
  • autonomy parameters
  • fleet software integration
  • routing algorithms
  • traffic orchestration
  • perception stack failures