Amazon Sr Data Scientist Professional Services 

China, Guangdong Province, Shenzhen 

400812924

The Senior Data Scientist, plays a crucial role in driving the development and implementation of cutting-edge generative artificial intelligence (GenAI) solutions for our clients. This position requires a deep understanding of machine learning, natural language processing, and generative models, combined with strong problem-solving skills and a passion for innovation.Key job responsibilities
1. Generative AI Model Development:
-Design and develop state-of-the-art 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.-Monitor and maintain deployed models, ensuring their continued performance and adherence to ethical and regulatory standards.5. Collaboration and Knowledge Sharing:-Mentor and guide junior data scientists, fostering knowledge sharing and promoting best practices in the field of generative AI.
-Contribute to the firm's thought leadership by publishing research papers, presenting at conferences, and participating in industry events.Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.Mentorship & Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.Work/Life Balance

- Master's or Ph.D. degree in Computer Science, Machine Learning, Artificial Intelligence, or a related quantitative field.
- Extensive experience (5+ years) 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.
- Excellent problem-solving, analytical, and critical thinking skills.
- Ability to communicate complex technical concepts to both technical and non-technical audiences.

- Experience with large language models, such as Claude, GPT, BERT, or T5.
- Knowledge of generative adversarial networks (GANs) and their applications in image generation or other domains.
- Familiarity with reinforcement learning techniques and their applications in generative AI.
- Understanding of ethical AI principles, bias mitigation techniques, and responsible AI practices.
- Experience with cloud computing platforms (e.g., AWS, GCP, Azure) and distributed computing frameworks (e.g., Apache Spark, Dask).
- Strong publication record in top-tier conferences and journals in the field of generative AI or related areas.
- Excellent communication, collaboration, and leadership skills.