AI Operations Specialist

Job Summary

The AI Operations Specialist is a junior-level role responsible for executing day-to-day physical AI operations, including data collection, model training support, physical edge deployment, and ongoing system maintenance. This role combines hands-on technical execution (robotics, digital billboards, IoT edge devices) with creative innovation to brainstorm and prototype new physical AI use cases. Working in close collaboration with external vendors and internal engineering teams, the specialist will support the entire lifecycle of physical AI solutions from initial concept to live site deployment.

Job Responsibilities 1

Coordinate and execute high-quality data collection, annotation, and preprocessing workflows to support the training of computer vision, NLP, and robotics models.

Support the physical installation, setup, and calibration of AI-enabled hardware, including digital billboards, edge compute nodes, camera networks, sensors, and robotic assets.

Monitor operational uptime and system health of deployed physical AI installations, performing first-line troubleshooting and escalating bugs to engineering teams.

Collaborate closely with technology vendors and hardware suppliers to coordinate deployments, test integrations, and ensure rapid resolution of hardware-software conflicts.

Actively contribute creative ideas and conceptualize new physical AI use cases (e.g., smart interactive billboards, automated facility management solutions, edge intelligence) that solve real-world problems.

Build and test rapid prototypes of AI-integrated physical setups, evaluating feasibility and demonstrating concepts to internal stakeholders.

Ensure all physical AI operations, data gathering activities, and device management practices comply with security, privacy, and Responsible AI guidelines.

Maintain a central log of physical deployments, system configurations, and operational incidents to support continuous product improvement.

Job Responsibilities 2

Additional Responsibilities 3

Job Knowledge & Skills

Fundamental understanding of machine learning pipelines, specifically data collection, model training, and edge inference.

Familiarity with Linux environments, command-line interfaces, and shell scripting.

Basic programming skills (preferably in Python or C++) for automating simple operational tasks.

Strong mechanical and electronic aptitude with the ability to safely assemble, connect, and configure physical IT/robotic components.

Creative mindset with the ability to brainstorm and articulate new use cases for emerging technologies.

Job Experience

0 to 2 years of experience (Junior level) in technical operations, software/hardware deployments, or robotics.

Hands-on experience with physical systems, edge hardware (e.g., Raspberry Pi, NVIDIA Jetson, Arduino), sensors, or basic electronics is highly preferred.

 Prior experience with data gathering, model labeling tools, or manual system testing is a strong plus.

Competencies

Education