Job ID: 2726519 | Amazon.com Services LLC
The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and innovative applied science manager with a strong background in responsible AI, deep learning and large language models (LLMs) techniques to lead and manage responsible AI development for world-class foundation models.
Key job responsibilities
As an applied science manager with the AGI team, you will hire and develop a team of world-class scientists to support the responsible AI initiatives at AGI. As a technical expert, you will strategize with other AGI teams on the best way to achieve the responsible AI objectives effectively and efficiently. You will build partnerships with other AGI teams and leverage relevant mechanisms to empower the team and deliver results at scale at AGI. You will coach your directs on scientific best practices and dive deep to unblock the team when needed. Your and your team's work will have a direct impact on AGI's business and customers through the foundation models we develop and deploy.
About the team
Our team's mission is to develop and deploy industry-leading foundation models that set the benchmark for the industry, comply with the relevant responsible RAI policies and delight our customers in the process.
BASIC QUALIFICATIONS- PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field, or Master's degree and 4+ years of building machine learning models or developing algorithms for business application experience
- 3+ years of scientists or machine learning engineers management experience
- Knowledge of ML, NLP, Information Retrieval and Analytics
- Experience with leading a science team required
- Experience with building large scale deep learning solutions for business required
- Experience programming in Java, C++, Python or related language required
PREFERRED QUALIFICATIONS- Experience building machine learning models or developing algorithms for business application
- Experience building complex software systems, especially involving deep learning, machine learning and computer vision, that have been successfully delivered to customers
- Experience with building and managing a science team required.
- Experience with leading a science team to conduct applied research in a large scale and dynamic corporate setting required.
- Strong track record of scientific publications at top-tier peer-reviewed conferences or journals required.
- Highly skilled at cross-functional collaborations including ability to communicate with diverse audiences, deal with ambiguities and resolve issues required.
- Experience with responsible RAI required
- Experience with deep learning modeling tools and workflows such as MxNet, TensorFlow, scikit-learn, Spark MLLib, numpy, scipy etc required.
- Experience with LLM model training and fine-tuning desired
- Experience with deep learning modeling techniques including Transformers required.
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