Job Summary: We are seeking an experienced and proficient AI Engineer with expertise in developing and deploying models at both edge and cloud environments, particularly in the field of computer vision applications.The ideal candidate will have a strong background in artificial intelligence, machine learning, and computer vision, along with hands-on experience in designing, training,and optimizing models for deployment in resource-constrained edge devices as well as scalable cloud infrastructures. Responsibilities: 1. Design, develop, and deploy cutting-edge AI models for edge and cloud environments, with a focus on computer vision applications. 2. Collaborate with cross-functional teams to understand project requirements and define AI solutions that meet business objectives. 3. Research and implement state-of-the-art algorithms and techniques in computer vision and deep learning. 4. Optimize models for inference speed, memory footprint, and power consumption on edge devices. 5. Develop and maintain scalable and efficient deployment pipelines for edge and cloud environments. 6. Evaluate and select appropriate hardware platforms and accelerators for AI model deployment. 7. Conduct performance analysis and debugging to ensure the reliability and accuracy of deployed models. 8. Stay updated with the latest advancements in AI, machine learning, and computer vision technologies. 9. Mentor junior engineers and provide technical guidance and support as needed. 10. Collaborate with product management and stakeholders to drive innovation and deliver high-quality solutions. Technical Requirements: 1. Bachelors degree in Computer Science, Electrical Engineering, or related field. Masters degree or Ph.D. preferred. 2. Minimum of 3-4 years of experience in AI/ML development, with a focus on computer vision applications. 3. Proficiency in deep learning frameworks such as TensorFlow, PyTorch, or Keras. 4. Strong programming skills in Python and proficiency in software development best practices. 5. Experience with edge computing platforms such as NVIDIA Jetson, Raspberry Pi, or Qualcomm Snapdragon. 6. Familiarity with cloud computing platforms such as AWS, Azure, or Google Cloud Platform. 7. Knowledge of deployment tools and technologies for edge and cloud environments (e.g.Docker, Kubernetes, AWS IoT Greengrass). 8. Hands-on experience with computer vision libraries and tools (e.g.,OpenCV, Dlib). 9. Understanding of hardware-accelerated inference frameworks (e.g.,NVIDIA TensorRT,Intel OpenVINO). 10. Excellent problem-solving skills and ability to work in a fast-paced collaborative environment. 11. Strong communication and interpersonal skills, with the ability to effectively communicate technical concepts to non-technical stakeholders.,
Employement Category:
Employement Type: Full time Industry: IT Services & Consulting Role Category: Not Specified Functional Area: Not Specified Role/Responsibilies: Artificial Intelligence Engineer