Amazon Web Services (AWS)
Sr. Applied Scientist , Amazon Connect
Amazon Web Services (AWS), Seattle, Washington, us, 98127
Sr. Applied Scientist, Amazon Connect
Amazon Web Services (AWS)
Do you want to join a team of innovative scientists to research and develop generative AI technology that would disrupt the industry? Do you enjoy dealing with ambiguity and working on hard problems in a fast‑paced environment? Amazon Connect is a highly disruptive cloud‑based contact center that enables businesses to deliver intelligent, engaging, dynamic, and personalized customer service experiences. The Agentic Customer Experience organization is responsible for weaving native‑AI across the Connect application experiences delivered to end‑customers, agents, and managers/supervisors. The Interactive AI Science team serves as the cornerstone for AI innovation across Amazon Connect, functioning as the sole science team that supports high‑impact product initiatives such as Amazon Q in Connect and Contact Lens.
As a Sr. Applied Scientist on this team, you will work closely with senior technical and business leaders from within the team and across AWS. You will distill insight from large data sets, conduct cutting‑edge research, and foster ML models from conception to deployment. You should have deep expertise in machine learning and deep learning broadly, and extensive domain knowledge in natural language processing, large‑language models, and Agentic AI. You must be comfortable quickly prototyping and iterating ideas to build robust ML models using TensorFlow, PyTorch, and AWS SageMaker. The ideal candidate can understand, implement, and innovate on state‑of‑the‑art Agentic AI based systems.
Basic Qualifications
3+ years of building machine‑learning models for business applications
PhD or Master’s degree with 6+ years of applied research experience
Experience programming in Java, C++, Python, or a related language
Experience with neural deep‑learning methods and machine‑learning techniques
Preferred Qualifications
PhD
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.
Amazon is an equal‑opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations.
Our compensation reflects the cost of labor across several U.S. geographic markets. The base pay for this position ranges from $150,400 per year in our lowest geographic market to $260,000 per 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; 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 other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits.
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Do you want to join a team of innovative scientists to research and develop generative AI technology that would disrupt the industry? Do you enjoy dealing with ambiguity and working on hard problems in a fast‑paced environment? Amazon Connect is a highly disruptive cloud‑based contact center that enables businesses to deliver intelligent, engaging, dynamic, and personalized customer service experiences. The Agentic Customer Experience organization is responsible for weaving native‑AI across the Connect application experiences delivered to end‑customers, agents, and managers/supervisors. The Interactive AI Science team serves as the cornerstone for AI innovation across Amazon Connect, functioning as the sole science team that supports high‑impact product initiatives such as Amazon Q in Connect and Contact Lens.
As a Sr. Applied Scientist on this team, you will work closely with senior technical and business leaders from within the team and across AWS. You will distill insight from large data sets, conduct cutting‑edge research, and foster ML models from conception to deployment. You should have deep expertise in machine learning and deep learning broadly, and extensive domain knowledge in natural language processing, large‑language models, and Agentic AI. You must be comfortable quickly prototyping and iterating ideas to build robust ML models using TensorFlow, PyTorch, and AWS SageMaker. The ideal candidate can understand, implement, and innovate on state‑of‑the‑art Agentic AI based systems.
Basic Qualifications
3+ years of building machine‑learning models for business applications
PhD or Master’s degree with 6+ years of applied research experience
Experience programming in Java, C++, Python, or a related language
Experience with neural deep‑learning methods and machine‑learning techniques
Preferred Qualifications
PhD
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.
Amazon is an equal‑opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations.
Our compensation reflects the cost of labor across several U.S. geographic markets. The base pay for this position ranges from $150,400 per year in our lowest geographic market to $260,000 per 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; 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 other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits.
#J-18808-Ljbffr