Perception and Infrastructure Software Intern

Key Skills

Amazon Elastic Compute Cloud-EC2, Amazon Simple Storage Service (S3), Computer Vision (CV), Docker, Infrastructure as code, Infrastructure-as-code-IaC, Kubernetes-K8s, Machine learning techniques, OpenCV, Python Programming, PyTorch, TensorFlow

Job Description

We are seeking a motivated Perception and Infrastructure Software Intern to join our team in the summer of 2025. This internship offers a unique opportunity to contribute to data collection software that runs on real robots across the United States 24/7/365. You will help us improve data collection systems on our fleet of robots, scale data upload systems, build out data pipelines in the cloud, and connect our vast quantities of robot sensor data to machine learning systems. You will work closely with our experienced engineers to streamline processes and build robust, scalable solutions.

Key Responsibilities:

• Run machine learning models on a large robotics dataset.
• Connect a large, growing dataset to machine learning labeling tools.
• Assist in the design and automation of cloud-based processing pipelines that perform various transformations on robot sensor data, including images and video.
• Optimize data preprocessing, indexing, and logging workflows for scalability and efficiency.
• Build new pipelines and convert existing pipelines to use Infrastructure as Code (IaC), add logging and monitoring systems

Qualifications

Required Skills

• Hands-on experience with AWS services, particularly those relevant to data pipelines (e.g. at least two of S3, EC2, Lambda).
• Familiarity with Git or other version control systems.
• Experience working with image, video, or other sensor data.
• Excellent communication skills and a collaborative mindset.

Preferred Skills

• Knowledge of computer vision libraries and frameworks (e.g., OpenCV, TensorFlow, PyTorch).
• Knowledge of containerization technologies (i.e. Docker, Kubernetes).
• Experience with Infrastructure as Code (IaC).
• Hands-on experience deploying software on robots or other edge devices.
• Background in robotics or real-time perception systems.
• Understanding of machine learning concepts and practices.