Job Information
Amazon Applied Scientist, AGI Info - Web & Knowledge Services in Bellevue, Washington
Description
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. 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.