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Amazon Knowledge Engineer, Artificial General Intelligence (AGI) Sports in Santa Barbara, California

Description

Amazon's Artificial General Intelligence organization is building the next generation of solutions and experiences with AI, shaping the way information is delivered, consumed and utilized.

That's where you come in. We're looking for a Knowledge Engineer to join us in sunny Santa Barbara and help us build the future. As a Knowledge Engineer, you will be responsible for identifying and executing on opportunities to make Alexa the World's best personal assistant with GenAI.

Key job responsibilities

In this role, you will:

  • Build out ontological constructs and ingest structured data to anchor Alexa experiences

  • Develop and manage complex data pipelines

  • Closely monitor KPIs and perform deep dives to uncover gaps, working with technical teams to implement solutions/improvements

  • Work closely with engineers, scientists and product managers to fine tune models and enhance underlying performance

-Work closely with ux, design and business development to bring forward new experiences

  • Help ideate, define and build new customer experiences

  • Leverage vertical-specific expertise to innovate on behalf of Alexa, enriching the ways customers receive information and take action

About the team

We sit at the intersection of Tech and Sports. We utilize our passion for sports, technical acumen and corporate athleticism to move quickly and intentionally in building the best sports assistant the world has ever seen.

Basic Qualifications

· Bachelor’s degree (or equivalent), in a quantitative or analytical field

· Concise clear written communication skills and excellent verbal communication ability

· Experience working on simultaneous projects with cross-functional teams

· Able to perform data analysis that drives conclusions and informs project priorities/deliverables

· Able to structure single data sets in models that facilitate data retrieval and aggregate analysis (e.g. Excel, SQL, SPARQL)

· Technical interest (e.g. MySQL, HTML, Python, Javascript, ETL, Excel)

Preferred Qualifications

  • Exposure to Large Language Model (LLM) and Natural Language Processing (NLP)

  • Strong interest in and knowledge of domestic and international sports

  • Ability to solve complex problems with analytical thinking

  • Ability to think critically

  • Demonstrated quantitative, systematic approach to solving problems

  • Ability to understand a problem before you approach it

  • Strong logical and conceptual thought processes

  • Ability to work autonomously with minimal supervision

Our Santa Barbara office is unique within Amazon. We balance the drive of a scrappy start-up with the immense resources of a cloud computing giant, and are looking for people with similar ambition.

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 $56,100/year in our lowest geographic market up to $125,500/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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