Sr. Applied Scientist, AGI Info
Job Description
Amazon’s Artificial General Intelligence (AGI) organization is developing a next-generation web-scale information retrieval system to support RAG applications across Amazon. We are looking for a Sr. Applied Scientist with expertise in information retrieval (IR) and ranking to join the team!If you are looking for an opportunity to develop innovative solutions to deep technical problems in web-scale IR, having a massive customer impact, this might be the role for you! As a Sr. Applied Scientist, you will work with smart, passionate colleagues in a fast-paced environment. You will invent, develop, and help deploy novel, scalable algorithms to advance the state-of-the-art in our IR stack. You will keep up with relevant research in the field of IR and publish your work in top-tier conferences. You will develop and help lead the execution of multi-year research roadmaps, enabling the team to focus on the right technical challenges to delight our customers.Key job responsibilitiesYou will lead a team of scientists to improve our RAG applications. You will be responsible for: (i) developing novel retrieval and ranking models and partnering closely with engineering to improve model performance; (ii) improve content and query understanding models to deliver improved signal to retrieval and ranking models; (iii) partner closely with content acquisition and client teams to ensure our dependencies are met and we’re delivering value to the end customers, enhancing information grounding for LLMs; (iv) develop science roadmaps for critical web search components; (v) publish your work and remain active in the academic communities; (vi) coach and develop junior scientists.A day in the lifeA mix of (i) technical deep dives: working with the team to develop the right models, setup good experiments, debug models, etc. (ii) coaching and development: providing feedback, setting up mechanisms to ensure the team’s success, and (iii) working with customers and dependency teams to ensure delivery.
Locations
- United States, CA, Sunnyvale, Sunnyvale, CA, United States
- United States, WA, Bellevue, Bellevue, WA, United States
Salary
Salary not disclosed
Estimated Salary Rangehigh confidence
250,000 - 400,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- - 3+ years of building machine learning models for business application experienceintermediate
- - PhD, or Master's degree and 6+ years of applied research experienceintermediate
- - Experience programming in Java, C++, Python or related languageintermediate
- - Experience with neural deep learning methods and machine learningintermediate
- - Experience with conducting research in a corporate settingintermediate
- - Experience with large scale machine learning systems such as profiling and debugging and understanding of system performance and scalabilityintermediate
Required Qualifications
- - 3+ years of building machine learning models for business application experience (experience, 3 years)
- - PhD, or Master's degree and 6+ years of applied research experience (experience, 6 years)
- - Experience programming in Java, C++, Python or related language (experience)
- - Experience with neural deep learning methods and machine learning (experience)
- - Experience with conducting research in a corporate setting (experience)
- - Experience with large scale machine learning systems such as profiling and debugging and understanding of system performance and scalability (experience)
Preferred Qualifications
- - Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc. (experience)
- - Experience with large scale distributed systems such as Hadoop, Spark etc. (experience)
- Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. (experience)
- Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/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. (experience)
Responsibilities
- You will lead a team of scientists to improve our RAG applications. You will be responsible for: (i) developing novel retrieval and ranking models and partnering closely with engineering to improve model performance; (ii) improve content and query understanding models to deliver improved signal to retrieval and ranking models; (iii) partner closely with content acquisition and client teams to ensure our dependencies are met and we’re delivering value to the end customers, enhancing information grounding for LLMs; (iv) develop science roadmaps for critical web search components; (v) publish your work and remain active in the academic communities; (vi) coach and develop junior scientists.
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Sr. Applied Scientist, AGI Info
Job Description
Amazon’s Artificial General Intelligence (AGI) organization is developing a next-generation web-scale information retrieval system to support RAG applications across Amazon. We are looking for a Sr. Applied Scientist with expertise in information retrieval (IR) and ranking to join the team!If you are looking for an opportunity to develop innovative solutions to deep technical problems in web-scale IR, having a massive customer impact, this might be the role for you! As a Sr. Applied Scientist, you will work with smart, passionate colleagues in a fast-paced environment. You will invent, develop, and help deploy novel, scalable algorithms to advance the state-of-the-art in our IR stack. You will keep up with relevant research in the field of IR and publish your work in top-tier conferences. You will develop and help lead the execution of multi-year research roadmaps, enabling the team to focus on the right technical challenges to delight our customers.Key job responsibilitiesYou will lead a team of scientists to improve our RAG applications. You will be responsible for: (i) developing novel retrieval and ranking models and partnering closely with engineering to improve model performance; (ii) improve content and query understanding models to deliver improved signal to retrieval and ranking models; (iii) partner closely with content acquisition and client teams to ensure our dependencies are met and we’re delivering value to the end customers, enhancing information grounding for LLMs; (iv) develop science roadmaps for critical web search components; (v) publish your work and remain active in the academic communities; (vi) coach and develop junior scientists.A day in the lifeA mix of (i) technical deep dives: working with the team to develop the right models, setup good experiments, debug models, etc. (ii) coaching and development: providing feedback, setting up mechanisms to ensure the team’s success, and (iii) working with customers and dependency teams to ensure delivery.
Locations
- United States, CA, Sunnyvale, Sunnyvale, CA, United States
- United States, WA, Bellevue, Bellevue, WA, United States
Salary
Salary not disclosed
Estimated Salary Rangehigh confidence
250,000 - 400,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- - 3+ years of building machine learning models for business application experienceintermediate
- - PhD, or Master's degree and 6+ years of applied research experienceintermediate
- - Experience programming in Java, C++, Python or related languageintermediate
- - Experience with neural deep learning methods and machine learningintermediate
- - Experience with conducting research in a corporate settingintermediate
- - Experience with large scale machine learning systems such as profiling and debugging and understanding of system performance and scalabilityintermediate
Required Qualifications
- - 3+ years of building machine learning models for business application experience (experience, 3 years)
- - PhD, or Master's degree and 6+ years of applied research experience (experience, 6 years)
- - Experience programming in Java, C++, Python or related language (experience)
- - Experience with neural deep learning methods and machine learning (experience)
- - Experience with conducting research in a corporate setting (experience)
- - Experience with large scale machine learning systems such as profiling and debugging and understanding of system performance and scalability (experience)
Preferred Qualifications
- - Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc. (experience)
- - Experience with large scale distributed systems such as Hadoop, Spark etc. (experience)
- Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. (experience)
- Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/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. (experience)
Responsibilities
- You will lead a team of scientists to improve our RAG applications. You will be responsible for: (i) developing novel retrieval and ranking models and partnering closely with engineering to improve model performance; (ii) improve content and query understanding models to deliver improved signal to retrieval and ranking models; (iii) partner closely with content acquisition and client teams to ensure our dependencies are met and we’re delivering value to the end customers, enhancing information grounding for LLMs; (iv) develop science roadmaps for critical web search components; (v) publish your work and remain active in the academic communities; (vi) coach and develop junior scientists.