LooprIQ Inspect is an AI application designed to automate quality and production processes on the factory floor. Using LooprIQ Inspect, customers can automate detection of defects in products, verify assembly of high-mix, low-volume parts and improve workforce results.
We have built a cutting-edge micro-service architecture where we leverage latest computer vision AI models in the backend to run inference on real-time video. store inference results in a scalable middleware and present them to a user friendly front-end whose experience is optimized for operators using the app in a factory setting. Data from the app is stored in a noSQL database which can be easily connected to customer's ERP system to derive analytics.
We are seeking a highly skilled and motivated Data Scientist to join our AI team. You will play a key role in developing and implementing computer vision algorithms and techniques to power LooprIQ Inspect which solves complex problems of our customers in the manufacturing and aerospace industries. You will also play a key role in guiding the direction of the company with cutting-edge development and innovation to help create other powerful solutions for our customers outside of this application.
If you are excited to work on these technologies and have proven experience in developing and deploying production grade computer vision and ML algorithms then we'd love to connect with you. You will have end to end design, development and delivery ownership of key components.
Please note: This role requires candidates to have existing US Citizenship or Permanent Residence (Green Card)
Responsibilities:
- Design and train deep learning models for object detection, image segmentation, and image classification tasks.
- Collaborate with cross-functional teams to understand project requirements and provide technical expertise in computer vision.
- Use Azure & ML Flow services to orchestrate complex computer vision pipelines and workflows for large-scale data processing and to track, manage, and reproduce experiments and models, ensuring reproducibility and scalability.
- Integrate computer vision models into production application using Python libraries and other relevant technologies.
- Optimize computer vision models for performance, efficiency, and accuracy on various hardware platforms, including server and edge deployments.
- Stay updated with the latest advancements in computer vision and machine learning research to enhance the company's capabilities.
- Collaborate with clients and stakeholders to understand their needs, propose solutions, and deliver results that meet their requirements.
Minimum Requirements:
- Bachelors, Master's or PhD in Computer Science, Informatics, Physics, or a related field.
- 1+ years of proven experience in computer vision, deep learning, and image processing, with a strong portfolio of projects.
- Proficiency in programming languages such as Python and experience with relevant computer vision libraries (e.g., OpenCV, TensorFlow, PyTorch).
- Solid understanding of computer vision concepts, including image classification, object detection, segmentation, and feature extraction.
- Experience with cloud platforms, especially Azure, for deploying and scaling computer vision models.
- Knowledge of containerization technologies (e.g., Docker, Kubernetes) for deploying computer vision models.
- Strong problem-solving skills and the ability to work on challenging computer vision tasks, while ensuring the right tools are used for the given task.
- Independent and self-driven with the ability to bring crazy ideas and innovation to the company, not just technical skills.
- Excellent communication skills and the ability to collaborate effectively with cross-functional teams and clients.
Joining Loopr AI offers an exciting opportunity to work with a dynamic team at the forefront of computer vision technology. You will have the chance to contribute to cutting-edge projects, collaborate with industry experts, and make a significant impact in solving real-world challenges using computer vision techniques.