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Sr. AI Engineer
2 months ago
- Design and develop machine learning pipelines for various tasks, including classification, regression, and natural language processing (NLP)
- Implement and experiment with different machine learning algorithms and techniques (e.g., supervised learning, unsupervised learning, deep learning)
- Pre-process and clean large datasets for model training and evaluation
- Train, evaluate, and optimize machine learning models using frameworks like TensorFlow, PyTorch, scikit-learn, and LangChain
- Integrate machine learning models into production systems and monitor their performance
- Design and develop machine learning pipelines for computer vision tasks, including object detection, image classification, and image segmentation
- Implement and experiment with different machine learning algorithms and techniques specific to computer vision, such as convolutional neural networks (CNNs)
- Collaborate effectively with data scientists, software engineers, and other stakeholders to ensure the successful development and deployment of machine learning solutions, particularly focusing on computer vision and LLM applications
- Communicate complex technical concepts to non-technical audiences
- Experience with cloud platforms (e.g., AWS, GCP, Azure) for deploying machine learning models
- Utilize database knowledge to efficiently store, retrieve, and manage large datasets used for training and evaluating machine learning models