We are seeking an experienced and innovative leader to spearhead our Generative AI initiatives. The Generative AI Leader and Expert will be responsible for driving the development and implementation of cutting-edge generative AI technologies, such as language models, image generation, and audio synthesis. This role requires a deep understanding of the latest advancements in generative AI, as well as the ability to partner with multiples teams of highly skilled researchers and engineers.
Key job responsibilities
- Develop and execute a comprehensive strategy for generative AI research and development initiatives.
- Collaborate with cross-functional teams, including product management, engineering, and data science, to align generative AI efforts with the company's overall goals and objectives.
- Provide thought leadership and guidance on generative AI trends, technologies, and best practices.
- Lead and oversee the research and development of innovative generative AI models, algorithms, and applications.
- Identify and explore new generative AI techniques and methodologies, such as transformer architectures, diffusion models, and generative adversarial networks (GANs).
- Collaborate with data scientists and engineers to ensure the efficient and effective implementation of generative AI solutions.
- Oversee the development and training of large-scale generative AI models, ensuring their accuracy, performance, and scalability.
- Implement effective techniques for model evaluation, bias detection, and mitigation.
- Collaborate with engineering teams to ensure the seamless deployment and integration of generative AI models into various applications and platforms.
- Develop and implement best practices for model management, versioning, and monitoring.
- Provide mentorship and guidance to team members, encouraging their professional growth and development.
- Foster cross-functional collaboration and knowledge sharing across the organization.
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.
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Work/Life Balance
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BASIC QUALIFICATIONS
- 3+ years of building machine learning models for business application experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning
- Bachelors degree in related field or equivalent years of experience
PREFERRED QUALIFICATIONS
- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale distributed systems such as Hadoop, Spark etc.
- PhD, or Master's degree and 6+ years of applied research experience
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.