Applied Scientist, AGI Knowledge Graphs, AGI Information - Knowledge Graphs
Applied Scientist, AGI Knowledge Graphs, AGI Information - Knowledge Graphs
Posted on :
26-05-2025
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1 Vacancy
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Job Description
Amazons AGI Information is seeking an exceptional Applied Scientist to drive science advancements in the Amazon Knowledge Graph team (AKG). AKG is re-inventing knowledge graphs for the LLM-era optimizing for LLM grounding and other LLM-based customer experiences. At the same time AKG is innovating to utilize LLMs in the knowledge graph construction pipelines to overcome obstacles that traditional technologies could not overcome.
As a member of the AKG Graph Construction team you will have the opportunity to work on interesting problems with immediate customer impact. The team is addressing challenges in knowledge mining data modeling fact verification and entity resolution. Your initial focus will be on web knowledge mining and entity resolution. You will also have the opportunity to work with scientists working on the other challenges and with the engineering teams that deliver the science advancements to our customers.
A successful candidate has a strong machine learning and LLM background is a master of state of the art techniques has a strong publication record has a desire to push the envelope in one or more of the above areas and has a track record of delivering to customers. The ideal candidate enjoys operating in dynamic environments is self-motivated to take on new challenges and enjoys working with customers stakeholders and engineering teams to deliver big customer impact shipping solutions via rapid experimentation and then iterating on user feedback and interactions.
Key job responsibilities
Key job responsibilities
As an Applied Scientist you will leverage your technical expertise and experience to demonstrate leadership in tackling large complex problems. You will collaborate with applied scientists and engineers to develop novel algorithms and modeling techniques to build the knowledge graph that delivers fresh factual knowledge to our customers and that automates the knowledge graph construction pipelines to scale to many billions of facts. Your first responsibility will be to solve entity resolution to enable conflating facts from multiple sources into a single graph entity for each real world entity. You will develop generic solutions that work fo all classes of data in AKG (e.g. people places movies etc.) that cope with sparse noisy data that scale to hundreds of millions of entities and that can handle streaming data. You will define a roadmap to make progress incrementally and you will insist on scientific rigor leading by example.
- 3 years of building models for business application experience
- PhD or Masters degree and 4 years of CS CE ML or related field experience
- Experience programming in Java C Python or related language
- Experience in any of the following areas: algorithms and data structures parsing numerical optimization data mining parallel and distributed computing high-performance computing
- Experience using Unix/Linux
- Experience in professional software development
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 including support for the interview or onboarding process please visit for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136000/year in our lowest geographic market up to $223400/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 This position will remain posted until filled. Applicants should apply via our internal or external career site.
As a member of the AKG Graph Construction team you will have the opportunity to work on interesting problems with immediate customer impact. The team is addressing challenges in knowledge mining data modeling fact verification and entity resolution. Your initial focus will be on web knowledge mining and entity resolution. You will also have the opportunity to work with scientists working on the other challenges and with the engineering teams that deliver the science advancements to our customers.
A successful candidate has a strong machine learning and LLM background is a master of state of the art techniques has a strong publication record has a desire to push the envelope in one or more of the above areas and has a track record of delivering to customers. The ideal candidate enjoys operating in dynamic environments is self-motivated to take on new challenges and enjoys working with customers stakeholders and engineering teams to deliver big customer impact shipping solutions via rapid experimentation and then iterating on user feedback and interactions.
Key job responsibilities
Key job responsibilities
As an Applied Scientist you will leverage your technical expertise and experience to demonstrate leadership in tackling large complex problems. You will collaborate with applied scientists and engineers to develop novel algorithms and modeling techniques to build the knowledge graph that delivers fresh factual knowledge to our customers and that automates the knowledge graph construction pipelines to scale to many billions of facts. Your first responsibility will be to solve entity resolution to enable conflating facts from multiple sources into a single graph entity for each real world entity. You will develop generic solutions that work fo all classes of data in AKG (e.g. people places movies etc.) that cope with sparse noisy data that scale to hundreds of millions of entities and that can handle streaming data. You will define a roadmap to make progress incrementally and you will insist on scientific rigor leading by example.
- 3 years of building models for business application experience
- PhD or Masters degree and 4 years of CS CE ML or related field experience
- Experience programming in Java C Python or related language
- Experience in any of the following areas: algorithms and data structures parsing numerical optimization data mining parallel and distributed computing high-performance computing
- Experience using Unix/Linux
- Experience in professional software development
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 including support for the interview or onboarding process please visit for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136000/year in our lowest geographic market up to $223400/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 This position will remain posted until filled. Applicants should apply via our internal or external career site.
Employment Type
Full-Time
Key Skills
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