AI/ML Data Annotation Intern
Job type: Full Time · Department: Engineering · Work type: On-Site
Bengaluru, Karnataka, India
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.
Someone with expertise in image-based data annotation for AI/ML, analytical visualization,
testing, and validation, preferably working with satellite imagery.
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.
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