Assistant Principal AI Engineer, Robotics Operations (Lab Safety, Assets & Field)

Job Overview

We are looking for a hands-on Assistant Principal AI Engineer to join AI.DA Strategic Technology Centre (STC)’s Next-gen Edge AI & Robotics (NEAR) Lab. Reporting to the Lead, Robotics Operations, this role is the technical operations backbone of the lab’s multi-robot “physical AI” environment — drones, quadrupeds, humanoids, and the edge AI stack on them.

You will be the primary in-charge for safety execution, asset and fleet readiness, vendor and procurement management, edge AI deployment support, and lab and field operations. The Lead, Robotics Operations retains overall safety authority, regulatory accountability (including CAAS UA permits), and operational leadership.

We are looking for a forward-thinking engineer who brings discipline and best practice to a fast-moving R&D environment. You will work directly with frontier robotics platforms in a small, technically deep team that collaborates with top robotics startups and academic partners. This is a hands-on, primarily on-site role, offered on a 2-year contract with opportunity for conversion. There is room to grow into broader operational leadership as the lab scales.

Key Responsibilities

1. Safety Execution & Administration (Priority)

• Administer safety processes under the Lead, Robotics Operations, including SOPs, emergency response, incident reporting, permits, and operations manuals.
• Conduct safety briefings, and track near-miss reports, safety metrics, and the safety champion rotation, escalating as required.
• Liaise with internal Safety, Legal, and Compliance teams and external regulators.

2. Asset Management & Fleet Readiness

• Own the asset register for all lab equipment, managing maintenance, calibration, firmware versioning, and end-of-life tracking.
• Perform first-line diagnostics and maintenance, covering batteries, cables, connectors, mechanical repairs, and component replacement.
• Perform first-line robotics technical work, including ground control setup (QGroundControl, Mission Planner), Ardupilot/PX4 configuration, vendor SDKs (Deep Robotics, Unitree, AgileX), firmware updates, and ROS/ROS2 troubleshooting.
• Support teams with hardware setup, sensor calibration, and pre-deployment checks, and coordinate vendor callouts, RMAs, and warranty claims.

3. Vendor & Procurement Management

• Own end-to-end procurement and vendor relationships across robotics platforms, drones, sensors, edge compute, and lab equipment (local and overseas), covering quotations, requisitions, tracking, delivery, and acceptance.
• Manage vendor service contracts, maintenance agreements, spares, and SLAs, and maintain procurement records, vendor register, renewal calendar, and budget tracking.
• Handle overseas shipments, customs, carnets, and temporary import/export arrangements, and coordinate with Finance, Procurement, and Legal to expedite approvals.

4. Edge AI Deployment Support

• Support the edge AI deployment pipeline on NVIDIA Jetson Orin and equivalent platforms under the Edge Compute Lead, including deploying policies, models, and runtimes, managing versioning and rollback, and executing model optimisation (TensorRT, quantisation, profiling).
• Maintain inference runtimes, dependencies, and reproducible builds, and support the sim-to-real CI/CD pipeline (validation, regression, field-readiness).

5. Lab & Field Operations

• Support the setup and continuous improvement of the lab, covering workspace planning, power, safety zones, layout, and specialised infrastructure (motion capture, gantries, harnesses, test rigs).
• Champion lab cleanliness and orderly workflows, applying operational best practices such as 5S or Six Sigma to improve efficiency, asset traceability, and process reliability.
• Anticipate operational needs as the lab scales, flagging capacity, infrastructure, or workflow risks early.
• Maintain clear operational documentation, and coordinate onboarding and visitor logistics (new hires, interns, postdocs, demo days, client visits).
• Coordinate field tests and demonstrations across equipment, permits, locations, manpower, and transport, and support on-site operations during trials (edge deployment, system bring-up, live troubleshooting).

Required Qualifications

• Degree in Engineering, Mechatronics, Robotics, EEE, Computer Science, or a related discipline. Diploma holders with 8+ years of relevant experience and demonstrated technical depth will be considered.
• 5+ years of experience across robotics or drone R&D operations, edge AI deployment, technical lab management, or field operations for unmanned systems.
• Hands-on experience with drones, mobile robots, or other robotic platforms, with practical familiarity with QGroundControl or Mission Planner, Ardupilot or PX4, and vendor SDKs. Working knowledge of ROS/ROS2.
• Familiarity with edge AI deployment on NVIDIA Jetson or equivalent (CUDA, TensorRT, containerised inference), and comfortable with LiPo/Li-ion batteries, wiring, soldering, and workshop tools.
• Strong organisational skills, with the ability to manage concurrent technical, vendor, and logistics workflows.
• Forward-thinking and proactive, with a strong safety mindset. Able to work independently on-site, with flexibility for field operations outside standard hours.

Preferred Qualifications

• Experience with Safety Management Systems (SMS) or comparable frameworks, and operational excellence frameworks (5S, Six Sigma, Lean) in a technical or lab environment.
• Experience setting up or managing robotics or hardware labs, and working with humanoid, quadruped, or manipulator platforms.
• Experience deploying ML models or learned policies to edge platforms in production or field settings, with familiarity in model optimisation and inference profiling.
• Experience supporting defence-related trials, evaluations, or field operations.
• Experience with overseas shipment of technical equipment, including customs, carnets, and temporary imports.