AI Engineer

Job Description (AI Engineer):Position Summary: As an AI Engineer at UXE, you will be responsible for designing, developing, and deploying cutting-edge AI systems with a primary focus on computer vision applications. You will work closely with our data science, engineering, and product teams to create efficient, scalable, and high-performance AI solutions that drive our products and services.Key Responsibilities:Develop and Optimize Computer Vision Algorithms:Design, implement, and refine computer vision algorithms for various applications such as object detection, image segmentation, and image classification.Enhance and optimize existing algorithms to improve accuracy, speed, and efficiency.AI System Deployment:Develop and deploy AI systems into production environments, ensuring they are robust, scalable, and maintainable.Collaborate with DevOps and software engineering teams to integrate AI solutions seamlessly into the company’s infrastructure.Performance Optimization:Write and optimize performant and efficient inference systems using Python or C++, ensuring low latency and high throughput.Implement hardware acceleration techniques (e.g., GPU, TPU) to enhance the performance of AI models.Collaboration and Communication:Work closely with cross-functional teams to understand project requirements and deliver solutions that meet business needs.Communicate technical concepts and solutions effectively to both technical and non-technical stakeholders.Research and Innovation:Stay updated with the latest advancements in AI, machine learning, and computer vision technologies.Conduct research and contribute to the continuous improvement of our AI capabilities.Qualifications:Required:Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or a related field.Proven experience in developing and deploying computer vision algorithms.Proficiency in programming languages such as Python and C++.Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, OpenCV, etc.Strong understanding of software development practices, including version control (Git), code reviews, and agile methodologies.Preferred:Ph.D. in a relevant field.Experience with cloud platforms (AWS, Google Cloud, Azure) and containerization technologies (Docker, Kubernetes).Knowledge of hardware acceleration technologies (e.g., CUDA, TensorRT).Strong problem-solving skills and the ability to think critically and creatively.Excellent communication and teamwork skills.