1. Advanced model development: design, train, and fine-tune state-of-the-art deep learning models for computer vision applications, addressing image recognition, object detection, and more
2. Performance evaluation: fine-tune models for speed, accuracy, and resource optimization
3. Deployment: deploy machine learning models to production environments, optimizing them for performance, scalability, and reliability
4. Management: manage tools and platforms for deploying and monitoring models, including cloud services, containerization, and orchestration
5. Collaboration: work closely with cross-functional teams, including product management and engineering, to integrate computer vision solutions into products
Requirements:
1. At least 3.5+ years of hands-on experience in developing, training, and deploying machine learning models, with a focus on computer vision tasks
2. Proficient in Python, with the ability to write clean, efficient, and scalable code
3. Proven experience with computer vision libraries like NumPy, Pandas, and OpenCV
4. Experience with techniques for enhancing, normalizing, and transforming images to improve model performance, such as SIFT, SURF, or HOG
5. Strong knowledge of deep learning frameworks like TensorFlow and PyTorch, with experience in transfer learning and fine-tuning pre-trained models
6. Understanding of CNN architectures like YOLO, Faster R-CNN, and Mask R-CNN for detecting and segmenting objects in images
7. Knowledge of generative models like GANs for image generation or style transfer
8. Proficiency in data structures relevant to processing and storing image data, such as trees, graphs, and multidimensional arrays
9. Solid foundation in linear algebra, probability, and statistics, with the ability to apply these principles to improve model accuracy and efficiency
10. Familiarity with distributed storage solutions like HDFS, S3, or Google Cloud Storage for managing large volumes of image and video data
11. Understanding of cloud platforms (AWS, GCP, or Azure), containerization (Docker), and orchestration tools (Kubernetes) for deploying and managing machine learning models
Skill(s) required
Data ScienceDeep LearningImage ProcessingMachine LearningPython
Fluid Analytics is an award-winning cleantech start-up, using cutting-edge technologies to help countries around the world tackle urban water pollution. The company's unique platform is deployed by cities to monitor the health of water infrastructure, the health of waterways (lakes, rivers, and coastlines), and public health. Fluid Analytics was recently awarded as the Global Top Innovator by the World Economic Forum, at this year's annual meeting in Davos, Switzerland. Come join our team of passionate individuals, striving to make cities around the world water resilient.
