Senior Computer Vision Engineer

About the Role:

We are seeking a highly skilled Senior Computer Vision Engineer to play a pivotal role in designing and building our next-generation, AI-powered video analytics platform. This is a hands-on, technical contributor role where you will leverage your deep expertise in multimedia frameworks to create high-performance, real-time solutions that push the boundaries of what's possible.

Key Responsibilities:

• Design, develop, and optimize robust, scalable video analytics pipelines using NVIDIA DeepStream, GStreamer, and TensorRT.
• Write high-quality, efficient, and maintainable code primarily in C/C++ and Python for real-time systems.
• Collaborate closely with product management and engineering teams to translate complex requirements into technical architecture and implementation plans.
• Perform debugging, profiling, and system optimization to maximize video streaming and AI inference performance.
• Integrate and optimize AI/ML models within production-grade video processing applications.
• Champion best practices through active participation in code reviews and contribute to the continuous improvement of our development processes.
• Ensure the reliability, scalability, and efficiency of solutions deployed in real-world environments.

Required Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
• 7+ years of professional software development experience.
• Strong, hands-on expertise with the NVIDIA DeepStream SDK, GStreamer framework, and TensorRT.
• Proven proficiency in C/C++ and Python programming for building performance-critical systems.
• Solid experience with video streaming protocols, multimedia frameworks, and developing AI-driven video applications.
• A proven track record of developing, shipping, and maintaining production software with a strong focus on performance and scalability.
• Excellent problem-solving abilities and strong collaboration skills.

Preferred Qualifications (Nice to Have):

• Experience with containerization technologies like Docker and deployment on edge devices.
• Familiarity with Video Management Systems (VMS) or applications in domains like smart cities, retail analytics, or industrial IoT.
• Practical experience with the integration and optimization of machine learning models into software pipelines.