Description :

Responsibilities :

- Design, develop, and deploy machine learning models for video processing and vision applications, including object detection, segmentation, tracking, and analysis.

- Work on vision-language models that combine visual and text data to create applications like image captioning, visual question answering (VQA), and other multi-modal tasks.

- Develop algorithms and models that can process, analyze, and understand video data efficiently.

- Leverage state-of-the-art deep learning frameworks (e.g., TensorFlow, PyTorch) to build and optimize computer vision models.

- Optimize models for real-time video processing, improving accuracy, speed, and scalability.

- Collaborate with other AI engineers, data scientists, and software developers to integrate vision-based models into production systems.

- Contribute to the full lifecycle of machine learning projects, from research and development to deployment and monitoring.

- Stay updated with the latest advancements in computer vision, video processing, and vision-language models, and apply best practices in AI model development.

- Collaborate with data scientists and engineers to develop and deploy ML models.

- Write clean, efficient, and reusable code using Python (mandatory) and C/Java (basic to intermediate level).

- Work with datasets to preprocess, clean, and transform data for ML pipelines.

- Implement basic ML/DL algorithms and help optimize model performance.

- Contribute to system-level design and architecture discussions for ML solutions.

- Stay up to date with trends in ML, DL, and AI technologies.

Qualifications :

- At least 4 to 17 years of proven experience as a Machine Learning Engineer or AI Engineer, with a strong focus on vision applications and video processing.

- Excellent programming skills in languages such as Python, C++, or similar.

- Solid background in computer science, including strong knowledge of algorithms, data structures, and software development principles.

- Hands-on experience with computer vision technologies, such as OpenCV, TensorFlow, PyTorch, and deep learning models for image/video recognition, segmentation, tracking, and analysis.

- Experience working with vision-language models (e.g., CLIP, Visual BERT, etc.) and multi-modal AI tasks.

- Familiarity with real-time video processing challenges and optimizations.

- Strong understanding of machine learning frameworks, including model development, training, and evaluation.

- Experience with version control tools like Git and collaborative development workflows.

- Excellent problem-solving skills, creativity, and a deep passion for AI and machine learning.

- Good communication skills and the ability to collaborate with cross-functional teams.