ML Ops Intern: Autonomous Warehouse Robots

Symbotic LLC; Wilmington (DE); On-site; USD 44,000 - 58,000; Part time

Job summary

Symbotic LLC is offering a Summer Internship in ML Operations to help build, scale, and deploy ML systems for autonomous warehouse robots. You will work with ML research, software, hardware, and operations teams to improve health, reliability, and performance of the robotic fleet.

Ideal candidates are pursuing a Master’s or PhD in a related field with strong Python or C++ coding skills, and familiarity with cloud platforms (GCP/Azure) and deployment tools like ONNX and TensorRT.

Qualifications

• Pursuing PhD or Masters in a related technical field.
• Coursework or project experience in CS, software eng, robotics, ML, or related discipline.
• Ability to deliver high‑quality, working code in Python or C++.

Responsibilities

• Architect and scale software platforms that support current and future autonomous capabilities.
• Collaborate with ML research and development teams to meet production deployment requirements.
• Optimize fleet deployment pipelines from merge requests through testing and rollout using ONNX, TensorRT, and custom hardware.
• Maintain and improve edge computing infrastructure for real‑time performance and reliability.
• Build ML pipelines for dataset curation, labeling, training, validation, and evaluation metrics.
• Develop simulation, diagnostics, monitoring, and alerting to accelerate system evaluation.
• Improve robotic software, compilation architectures, and Docker Compose configurations.

Skills

Python

C++

GCP

Azure

ONNX

TensorRT

Docker

Edge computing

Collaboration

Education

Pursuing PhD or Master's Degree

Tools

ONNX

TensorRT

Docker

Edge computing platforms

Job description

Symbotic LLC is offering a Summer Internship in ML Operations to help build, scale, and deploy ML systems for autonomous warehouse robots. You will work with ML research, software, hardware, and operations teams to improve health, reliability, and performance of the robotic fleet.

Ideal candidates are pursuing a Master’s or PhD in a related field with strong Python or C++ coding skills, and familiarity with cloud platforms (GCP/Azure) and deployment tools like ONNX and TensorRT.