AI Engineer – Computer Vision

About the Role

Position: AI Engineer (Computer Vision)
Department: AI/ML Engineering
Experience Level: 2 to 5 years

We are looking for an AI Engineer with strong expertise in computer vision to join our team and build vision-based intelligence systems for real-world industrial applications. The ideal candidate will have hands-on experience designing and deploying models for object detection and temporal/motion monitoring, including systems that track and record human movement in dynamic environments such as assembly manufacturing lines.

Key Responsibilities

· Design, develop, and deploy computer vision models for detection, tracking, and temporal monitoring use cases

· Build and optimize systems that track and record movement of individuals (e.g., operator/worker movement tracking) in manufacturing or assembly-line settings for process monitoring, safety, and efficiency analysis

· Work with video streams and time-series visual data to detect patterns, anomalies, and events over time

· Train, fine-tune, and evaluate deep learning models, including transformer-based architectures, for vision tasks

· Optimize models for inference speed, memory footprint, and deployment on edge/production environments

· Collaborate with cross-functional teams (product, hardware, operations) to translate business requirements into deployable AI solutions

· Maintain data pipelines for annotation, training, and continuous model evaluation

· Stay current with state-of-the-art research in computer vision and applied AI, and evaluate its applicability to ongoing projects

Required Qualifications

· Proven experience working on computer vision projects (academic, research, or industry)

· Hands-on experience with vision-based models for object/person detection and temporal monitoring (e.g., tracking movement, activity recognition, event detection over video sequences)

· Demonstrated experience on projects involving tracking and recording movement of people — ideally in manufacturing, assembly-line, or similar operational/industrial settings

· Strong understanding of AI/ML fundamentals — supervised/unsupervised learning, neural network architectures, evaluation metrics, etc.

· Practical experience with model training workflows (data preparation, augmentation, loss functions, hyperparameter tuning)

· Working knowledge of transformer-based models (e.g., ViT, DETR, or similar) as applied to vision tasks

· Experience with model optimization techniques — quantization, pruning, distillation, or conversion for efficient inference (e.g., ONNX, TensorRT)

· Proficiency in Python and common deep learning frameworks (PyTorch, TensorFlow)

· Familiarity with tools/libraries such as OpenCV, YOLO, Detectron2, MMDetection, or similar

Job Types: Full-time, Permanent

Education:

• Bachelor's (Preferred)

Work Location: In person