Computer Vision Engineer
Recrew AI
Bangalore Urban, Karnataka, India0–2 yrs1h agovia LinkedIn
About the Role
- Develop cutting-edge image processing algorithms for ground-based telescopes used in satellite navigation systems.
- Design ML/DL models for astronomical object detection, focusing on star tracking and celestial object classification to support ADCS systems.
- This role offers direct impact on space technology for satellite operations, with exposure to hardware integration and algorithm optimization for real-sky conditions.
Key Responsibilities
- Design and develop high-performance ML/DL models for object detection in astronomical images, identifying stars as spots/blobs and objects as streaks/lines.
- Implement detection and classification algorithms to distinguish between stellar blobs and object streaks with sub-pixel accuracy.
- Train and test models using synthetic and real astronomical image datasets.
- Document model performance evaluation and report coordinate retrieval with sub-pixel precision.
- Optimize algorithms for real-sky conditions including various signal and noise environments.
- Collaborate with hardware teams to integrate image processing solutions with ADCS components.
- Deliver technical documentation and briefings on algorithm performance and implementation.
Requirements & Tech Stack
- Strong proficiency in Python with Object-Oriented Programming (OOP) implementation skills.
- Academic or project experience with CNN architectures for object detection and classification.
- Hands-on experience with PyTorch and TensorFlow/Keras through coursework or personal projects.
- Familiarity with scientific Python libraries: Astropy, Scikit-learn, and SciPy.
- Strong analytical and problem-solving skills with ability to learn independently.
- Git repository management experience and version control best practices.
- Experience with OpenCV for computer vision tasks and image preprocessing.
Qualifications
- Bachelor's or Master's degree in Electronics, Physics, Data Science, Astronomy, or related technical field.
- 0-2 years of experience with image processing algorithms and machine learning.
Nice to Have
- Understanding of astronomical images and signal/noise conditions in real-sky imaging.
- Knowledge of Bayesian methods and probabilistic models for orientation estimation.
- Academic projects or internships in aerospace, astronomy, or satellite imaging applications.