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.