Applied Scientist, AGI Info - Web & Knowledge Services

Company:  Amazon
Location: Dallas
Closing Date: 15/10/2024
Salary: £100 - £125 Per Annum
Hours: Full Time
Type: Permanent
Job Requirements / Description

Applied Scientist, AGI Info - Web & Knowledge Services

Job ID: 2796502 | Amazon.com Services LLC

Amazon’s AGI Information is seeking an exceptional Applied Scientist to develop 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 Science team, you will have the opportunity to work on interesting cutting edge problems with immediate customer impact. The team is addressing challenges in automating gap detection, data ingestion, fact verification, query optimization and entity resolution. You will work with the entity resolution team to develop generic entity resolution models that work for every class of data in AKG (e.g., people, places, movies, etc.), that scale to hundreds of millions of entities, and that work incrementally. You will collaborate with other scientists to develop entity representations, training data and matching models to solve the problem. You will also work to optimize models to be performant and cost-effective in production.

A successful candidate has a strong machine learning and LLM background, identifies and adapts state of the art techniques to solve new problems, builds POCs quickly to identify promising techniques and reject ideas that do not work, and enjoys collaborating with engineering teams to ship solutions incrementally via rapid experimentation. A successful candidate is an avid reader of the scientific literature and works to publish in peer reviewed conferences.

Key job responsibilities
As an Applied Scientist, you will apply scientific rigor to your work. You will work incrementally, setting up and executing experiments informed by rigorous failure space analysis of prior experiments. You have a knack for writing clear, succinct and informative reports of your experiments. You collaborate and seek guidance from other scientists on your team to define the next experiments. You work with engineers to understand deployment requirements and constraints, and work to address them. You work continuously with customers and stakeholders to simplify and adapt to deliver for our customers.

BASIC QUALIFICATIONS

- 3+ years of building models for business application experience
- PhD, or Master's 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

PREFERRED QUALIFICATIONS

- Experience using Unix/Linux
- Experience in professional software development
- PhD in Computer Science, Electrical Engineering, or Mathematics with specialties in machine learning and natural language processing
- 3+ years experience in building machine learning and deep learning models for large scale customer facing product of features
- Hands-on experience with LLMs
- Hands-on experience with Semantic Web technologies and graph databases (e.g., Cypher, SPARQL, RDF)
- Publications at peer-reviewed conferences (e.g. ACL, EMNLP, NAACL, NeurIPS, ICLR, ICML, AAAI, IJCAI, SIGIR, ISWC)

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.

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