Job VC

We are looking for a Computer Vision Engineer with strong experience in deep learning and production computer vision systems.
The role involves developing and bringing computer vision models into production, covering the full lifecycle from training and evaluation to deployment and system integration.
Responsibilities:
Develop and improve Computer Vision and Machine Learning models
Design and implement solutions for object detection, classification, segmentation, and tracking
Work with large-scale image, video, and telemetry datasets
Prepare, process, and maintain datasets for model training and evaluation
Manage model training, validation, and testing workflows
Optimize models for production deployment and real-time performance
Integrate ML models into software services, applications, and APIs
Analyze model performance and identify opportunities for quality improvement
Participate in the design and architecture of AI components within the product ecosystem
Collaborate closely with Backend, Infrastructure, Data, and Product Engineering teams
Contribute to the development of MLOps practices and the end-to-end machine learning lifecycle.
Requirements:
3+ years of experience in computer vision
High proficiency in Python
Strong experience with deep learning and the PyTorch framework for computer vision tasks
Research experience in computer vision with a focus on delivering results
Ability to work independently or within a small team, with a strong sense of ownership over results
Nice to Have:
Experience working with thermal imaging data (thermal cameras, infrared imagery) would be an advantage
Experience with deep learning solutions for detection, tracking, image retrieval, and segmentation tasks
Understanding of geometric computer vision principles
Model optimization: quantization, pruning, neural network compilers
Hands-on experience implementing low-level CV algorithms
Experience with sensor fusion (IMU, magnetometer, GNSS, camera)
Knowledge of C++