Robotics & AI Engineering Lead — Real-Time Vision & ROS 2

Jabil; Lexington (KY); On-site; USD 140,000 - 190,000; Full time

Benefits offered by this job

Base salary

Annual bonus

Medical, dental, vision insurance

401K match

Employee stock purchase plan

Paid time off

Tuition reimbursement

Life/AD&D insurance

Commuter benefits

Employee assistance program

Pet insurance

Adoption assistance

Merit increases

Volunteer opportunities

Job summary

Badger Technologies, a division of Jabil, is seeking an Engineering Lead to direct ROS/CV/AI-driven robotics projects onsite in Lexington, KY. You will lead a team of ROS and CV/AI developers to design, train, and deploy real-time vision models and robot control pipelines, integrating AI with hardware for production-scale outcomes.

You will own the vision pipeline, drive scalable software, and guide architecture decisions to ensure low latency, robust performance, and seamless edge deployment

Qualifications

• Bachelor's degree in a technical field; Master’s preferred.
• 12+ years in robotics software, AI/ML, autonomous systems, or related fields with leadership.
• Strong ROS/ROS 2 architecture for production-grade robotics.

Responsibilities

• Build and sustain smart robotic systems and data services.
• Direct a team of ROS and CV/AI developers in an Agile environment.
• Own the vision pipeline and design scalable software for real-time perception and robot control.
• Consult on system architectures to deliver high-quality products.

Skills

ROS/ROS 2

Computer vision

Deep learning

3D vision

Sensor fusion

C++

Python

Robotics simulators

Education

Bachelor's degree in a technical field

Master’s degree preferred

Tools

Isaac Sim

Gazebo

Kubeflow

MLflow

AWS

GCP

Azure

Job description

Badger Technologies, a division of Jabil, is seeking an Engineering Lead to direct ROS/CV/AI-driven robotics projects onsite in Lexington, KY. You will lead a team of ROS and CV/AI developers to design, train, and deploy real-time vision models and robot control pipelines, integrating AI with hardware for production-scale outcomes.

You will own the vision pipeline, drive scalable software, and guide architecture decisions to ensure low latency, robust performance, and seamless edge deployment