AI Engineer
3 hours ago
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.
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