AI/ML Data Annotation Intern

Digantara is a leading Space Surveillance and Intelligence company focused on ensuring

orbital safety and sustainability. With expertise in space-based detection, tracking,

identification, and monitoring, Digantara provides comprehensive domain awareness across

regimes, allowing end users to have actionable intelligence on a single platform. At the core of

its infrastructure lies a sophisticated integration of hardware and software capabilities aligned

with the key principles of situational awareness: perception (data collection), comprehension

(data processing), and prediction (analytics). This holistic approach empowers Digantara to

monitor all Resident Space Objects (RSOs) in orbit, fostering comprehensive domain

awareness.

Digantara is seeking an AI/ML Data Annotation Intern to accurately annotate features such

as blobs and streaks in SSA imagery captured from ground-based and space-based sensors. The

intern will pre-process and tile the imagery into appropriate tile sizes to make the data machinelearning-ready. The role will also involve partially training, testing, and validating AI/ML

models, along with reporting bugs and identifying hyperparameters that need to be tuned.

• Competitive incentives, galvanizing workspace, blazing team, frequent outings - pretty

• much everything you have heard about a start-up, and you get to work on space

• technology.

• Hustle in a well-funded start-up, allowing you to take charge of your responsibilities

  and create your moonshot.

  Ideal Candidate:

• Someone with expertise in image-based data annotation for AI/ML, analytical visualization,

• testing, and validation, preferably working with satellite imagery.

  Responsibilities

• Accurately annotate features such as blobs and streaks in SSA imagery using manual

  or semi-automatic annotation techniques.

• Use the existing AI/ML models or classical image processing pipelines to perform

  semi-automatic annotation of the features.

• Pre-process and tile the imagery according to model input requirements.

• Assist in training and testing the existing models using the prepared datasets, and

  document performance benchmarks for detection and classification tasks.

• Report errors and identify hyperparameters that need to be tuned during training and

  evaluation.

• Bachelor’s or Master’s degree in Electronics, Computer Science, Data Science,

• Artificial Intelligence, Statistics, Astronomy, or any relevant field.

• Final-year students (available for a full-time internship), freshers, or candidates with 0–

  2 years of academic, research, or industry experience, with a strong interest or aptitude

  in data annotation, image labelling, machine learning, and deep learning.

• Basic understanding of computer vision concepts and satellite imagery, including

  different signal and noise conditions.

• Strong analytical, problem-solving, and critical-thinking skills.

• Hands-on experience in image data annotation using tools such as CVAT, Roboflow,

  or similar annotation platforms.

• Proficiency in Python, OpenCV, PyTorch or TensorFlow/Keras; familiarity with

  libraries such as Astropy, Scikit-learn, SciPy, and other relevant libraries is an

  advantage.

• Familiarity with developing deep learning networks such as CNNs for detection,

  segmentation, and classification tasks.

• Familiarity with Git and version-control workflows is an advantage.

• Ability to work in a mission-focused, operational environment.

• Ability to think critically and make independent decisions.

• Interpersonal skills to enable working in a diverse and dynamic team.

• Maintain a regular and predictable work schedule.

• Writing and delivering technical documents and briefings.

• Verbal and written communication skills as well as organizational skills.

• Travel occasionally as necessary.