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Description

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.

-Collaborate with cross-functional teams to ensure the successful deployment and integration of generative AI models into client solutions.

-Monitor and maintain deployed models, ensuring their continued performance and adherence to ethical and regulatory standards.

5. Collaboration and Knowledge Sharing:

-Collaborate with data engineers, software engineers, and subject matter experts to develop innovative solutions leveraging generative AI.

-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.

About the team

About AWS

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.

Why AWS?

Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

Inclusive Team Culture

Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.

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

We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.

AWS Sales, Marketing, and Global Services (SMGS) is responsible for driving revenue, adoption, and growth from the largest and fastest growing small- and mid-market accounts to enterprise-level customers including public sector. The AWS Global Support team interacts with leading companies and believes that world-class support is critical to customer success. AWS Support also partners with a global list of customers that are building mission-critical applications on top of AWS services.

Basic Qualifications

• 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.

Preferred Qualifications

• 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.