ML Ops Intern (Summer): Edge & Fleet Deployment

Symbotic; Wilmington, Northern (MA, KY); Hybrid; USD 44,000 - 58,000; Full time

Benefits offered by this job

Housing benefits

Transportation benefits

Job summary

Symbotic is offering a Summer Intern - Machine Learning Ops to join the ML Operations team within the Software organization. You will help build, scale, and deploy machine learning systems that improve health, reliability, and performance of our autonomous warehouse robot fleet.

You will collaborate across ML research, software, hardware, and operations to scale monitoring and deployment infrastructure. The internship emphasizes mentorship, professional development, and exposure to end-to-end

Qualifications

• Pursuing PhD or Master’s degree in a related field.
• Coursework or project experience in CS, software engineering, robotics, ML.
• Proficiency in Python or C++ with ability to deliver working code.
• Experience with cloud infrastructure (GCP/Azure).
• Familiarity with ML deployment tech (ONNX, TensorRT, Docker).
• Willingness to travel up to 10% and relocations as needed.

Responsibilities

• Architect and scale software platforms supporting autonomous capabilities.
• Collaborate with ML research and development teams to meet production requirements.
• Optimize deployment pipelines for robotic fleets using ONNX, TensorRT, and custom hardware.
• Maintain edge computing infrastructure for real-time performance and reliability.
• Build ML pipelines for data curation, labeling, training, validation, and evaluation.

Skills

Python or C++

Collaboration skills

Problem solving

Education

Pursuing PhD or Masters

Tools

ONNX

TensorRT

Docker

Edge computing platforms

Job description

Symbotic is offering a Summer Intern - Machine Learning Ops to join the ML Operations team within the Software organization. You will help build, scale, and deploy machine learning systems that improve health, reliability, and performance of our autonomous warehouse robot fleet.

You will collaborate across ML research, software, hardware, and operations to scale monitoring and deployment infrastructure. The internship emphasizes mentorship, professional development, and exposure to end-to-end