Autonomous has a project oriented organizational structure, which ensures high flexibility and productivity. We are specialized in various domains: Artificial intelligence, Mobile software development, Cloud computing, R&D Robotics. Together with private companies and public authorities we have managed to develop research and development projects that have a key contribution in the development of society.

Enhancing drones’ autopilot perception abilities with edge computing DNN trained on synthetic generated data
Paid internship at Autonomous · Starts after academic term
  • – Artificial Intelligence
  • – Embedded & Internet of Things
  • – Electrical Engineering
  • room București
Required skills:

computer vision python architecture unreal electronics microcontrolere

Join our cutting-edge research team as an intern to contribute to our innovative project focused on creating synthetic aerial environments for training deep neural networks, and enhancing the autopilots with complex reasoning abilities to perform autonomous tasks. This internship offers a unique opportunity to work on a project aimed at enhancing drone autonomy through advanced image analysis and machine learning techniques. You will work closely with experts in the field, gain hands-on experience with state-of-the-art technology, and contribute to groundbreaking research.

Internship Duration

3-6 months

Number of Positions



Automated Data Generation and Annotation:

  • Synthetic Dataset Creation: Utilize 3D simulation environments to generate complex scenes with aerial images with varying parameters (e.g., weather conditions, camera orientations, altitudes).
  • Automated Ground Truth Annotation: Apply and refine algorithms to generate accurate bounding boxes and annotations for training datasets.
  • Quality Assurance: Validate the generated images and annotations to ensure they meet the project’s quality standards.

Deep Learning Model Design and Training:

  • Model Development: Design DNN architecture and assist in training deep neural networks using the generated synthetic datasets, focusing on object detection tasks.
  • Optimization: Work on optimizing DNN models for deployment on low-power devices such as Google Coral micro boards, Raspberry PI, NXP NavQPlus AI/ML Companion Computer
  • Performance Evaluation: Conduct tests and evaluations to measure the performance of trained models in simulation environments and real-world scenarios.

Hardware Development, Integration and Testing:

  • Drone Hardware Integration: Assist in integrating edge computing hardware (e.g., Coral Mini Board, Raspberry PI, NXP NavQPlus AI/ML Companion Computer, Coral Camera, RPi Camera) with drone systems such as NXP RDDRONE-FMUK66
  • Simulation and Real-World Testing: Participate in both hardware-in-the-loop (HIL) simulations and real-world drone flight tests to validate system performance in simulators such as AirSim/Unreal Engine 4.6
  • Troubleshooting: Identify and resolve hardware and software issues during integration and testing phases.


Educational Background

Pursuing or recently completed a degree in Computer Science, Electrical Engineering, Robotics, Architecture or related fields.

Technical Skills needed for the entire internship team:

  • Experience with Python and relevant libraries (e.g., OpenCV, TensorFlow, PyTorch).
  • Familiarity with 3D simulation environments (e.g., AirSim, Unreal Engine).
  • Knowledge of deep learning frameworks and model training.
  • Understanding of hardware integration and communication protocols (e.g., MAVLink).
  • Experience with drone technology and image processing.
  • Previous work or projects involving synthetic data generation.
  • Hands-on experience with edge computing devices and embedded systems.

Soft Skills

Strong problem-solving abilities, attention to detail, and effective communication skills. Ability to work independently and as part of a team.


  • Gain practical experience in a highly interdisciplinary and innovative research project.
  • Work with state-of-the-art technology and tools.
  • Mentorship from experienced professionals and researchers.
  • Opportunity to contribute to publications and technical reports.
  • Training and to exam for remote drone pilot certificate A1-A3, A2

Application Process

To apply, please answer the interview questions and submit your resume and relevant experience, and any supporting documents (e.g., project portfolios, GitHub repositories). Applications will be reviewed on a rolling basis until all positions are filled.