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Amazon Applied Scientist, AZA Team in Seattle, Washington

Description

The AZA Team is responsible for A to Z Assistant (AZA), an AI-powered virtual assistant designed to help Amazon employees find information and complete tasks more efficiently, freeing up time to focus on serving customers. With AZA, we are building on our search improvements and making it faster and easier than ever to get answers and complete tasks. Using natural language, employees simply ask AZA for what they need or are trying to do.

You will engage in cutting-edge natural language technologies, driving innovation and developing experimental solutions that surpass business challenges. You will partner and collaborate across multiple Generative AI solutions within PXT organizations, ensuring meaningful impact. In this role, you will work closely with Scientists, Engineers, Product Managers, and UX teams to implement highly sophisticated, Generative AI-based solutions that address complex problems and elevate strategic high visibility initiatives.

Key job responsibilities

Leverage your technical expertise to demonstrate leadership in addressing large-scale, complex Generative AI challenges by utilizing Bedrock LLM and other industry-leading solutions. Set strategic direction and collaborate with Applied Scientists and Engineers to develop innovative algorithms and advanced modeling techniques.

Partner with software engineering teams to design, develop, and integrate large-scale AI solutions that drive business impact and operational efficiency.

Cultivate a deep, comprehensive understanding of large-scale technological solutions to which you will contribute, ensuring seamless interaction with components managed by cross-functional teams.

Proactively anticipate challenges and navigate complexities, effectively prioritizing tasks, managing trade-offs, and influencing the development of advanced AI-driven advertising products that extend beyond the immediate scope of your team.

Basic Qualifications

  • PhD, or Master's degree and 4+ years of applied science experience

  • 2+ years of building Generative Ai based solutions for business applications experience

  • Experience programming in Python or related language

  • Experience with neural deep learning methods and machine learning

  • Experience in building large scale Generative Ai based solutions

Preferred Qualifications

  • 5+ years of applied research experience

  • Experience with modeling tools such as R, scikit-learn, PyTorch, Tensorflow, etc.

  • Experience in building chatbot solutions, speech recognition, machine translation and natural language processing systems

  • Experience with MultiModality content format such as image, audio, video transformation and ingestion in vectorDB for most relevant retrieval

  • Experience in implementation of advance features like personalization and reinforcement learning

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 $136,000/year in our lowest geographic market up to $222,200/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.

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