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Software Engineer Intern (AI/ML), PTLab

CollaboratorTechSoftware26-PTLab-3805
locationThành phố Hồ Chí Min...
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Mô tả công việc

A Software Engineer (AI/ML) Intern at PT Lab will work at the intersection of code and physical systems. You will contribute directly to building the MVP of our True Core System (TCS) — the software backbone of our physiotherapy robotics platform — while also helping optimize the data engineering pipelines that power our Embodied AI track. This is a hands-on, high-ownership role for engineers who want to ship real code that runs on real hardware.

You Will:

  • Contribute to the development and testing of the TCS MVP, including backend logic, data flows, and integration with hardware control interfaces.
  • Build and optimize data engineering pipelines for ingesting, processing, and curating high-fidelity physical interaction data.
  • Assist in implementing and validating machine learning components for real-time inference on resource-constrained hardware.
  • Collaborate with the mechanical, electronics, and integration engineers to ensure software-hardware reliability across the stack.
  • Write clean, well-documented code and participate in code reviews with the full engineering team.
  • Support dataset curation and annotation workflows during the 4-month data collection sprint.

Yêu cầu

Basic Qualifications:

  • Currently pursuing a Bachelor's degree in Software Engineering, Computer Science, AI/Machine Learning, or a related field.
  • Proficiency in Python and experience with at least one deep learning framework (PyTorch or TensorFlow).
  • Familiarity with data pipeline tools and practices (ETL, data cleaning, structured storage).
  • Solid foundation in the mathematics behind machine learning: linear algebra, probability, and optimization.
  • Ability to work independently, move fast, and communicate clearly in English.
Preferred Skills and Experience:

  • Prior internship or project experience deploying ML models in non-trivial environments (robotics, embedded systems, or simulation).
  • Experience with edge AI concepts such as model quantization or deployment on embedded hardware (e.g., Nvidia Jetson).
  • Familiarity with ROS/ROS2 or other robotics middleware.
  • Experience with version control (Git) and collaborative software development workflows.
  • A portfolio or GitHub showing practical AI/software projects, especially those involving physical or sensor data.