亚马逊Data Scientist, Data Intelligence, Professional Services GCR

任职要求

基本任职资格
- Master's or Ph.D. degree in Computer Science, Machine Learning, Artificial Intelligence, or a related quantitative field.
- 4+ years of experience in developing and deploying machine learning models, with a strong focus on generative AI techniques.
- Proficiency in programming languages such as Python, PyTorch, or TensorFlow, and experience with deep learning frameworks.
- Strong background in natural language processing, computer vision, or multimodal learning.
- Ability to communicate technical concepts to both technical and non-technical audiences.

优先任职资格
- Experience with large language models, such as Claude, GPT, BERT, or T5.
- Familiarity with reinforcement learning techniques and their applications in generative AI.
- Understanding of ethical AI princi…

工作职责

1. Generative AI Model Development:
-Design and develop generative AI models, including language models, image generation models, and multimodal models.
-Explore and implement advanced techniques in areas such as transformer architectures, attention mechanisms, and self-supervised learning.
-Conduct research and stay up-to-date with the latest advancements in the field of generative AI.

2. Data Acquisition and Preprocessing:
-Identify and acquire relevant data sources for training generative AI models.
-Develop robust data preprocessing pipelines, ensuring data quality, cleanliness, and compliance with ethical and regulatory standards.
-Implement techniques for data augmentation, denoising, and domain adaptation to enhance model performance.

3. Model Training and Optimization:
-Design and implement efficient training pipelines for large-scale generative AI models.
-Leverage distributed computing resources, such as GPUs and cloud platforms, for efficient model training.
-Optimize model architectures, hyperparameters, and training strategies to achieve superior performance and generalization.

4. Model Evaluation and Deployment:
-Develop comprehensive evaluation metrics and frameworks to assess the performance, safety, and bias of generative AI models.
-Collaborate with cross-functional teams to ensure the successful deployment and integration of generative AI models into client solutions.

5. Collaboration and Knowledge Sharing:
-Collaborate with data engineers, software engineers, and subject matter experts to develop innovative solutions leveraging generative AI.
-Contribute to the firm's thought leadership by presenting at conferences, and participating in industry events.