Applied Scientist II - Multimodal Information Retrieval/Search, AGI (Level 5)
Apply NowCompany: Amazon
Location: Boston, MA 02115
Description:
We are seeking a passionate, talented, and inventive scientist to join the Amazon AGI team. As an Applied Scientist, you'll be at the forefront of developing intelligent systems that can seamlessly process, understand, and retrieve multimodal information.
We're seeking a creative problem-solver who's excited about architecting novel deep learning solutions for multimodal search and retrieval. You'll work on advancing the state-of-the-art in vision-language models and multimodal embeddings, while developing efficient and scalable algorithms for cross-modal retrieval. Your role will involve creating innovative solutions for multimodal ranking and relevance, ultimately building the next generation of multimodal search systems that can understand and process information the way humans do.
You'll collaborate with a talented team of researchers and engineers, contribute to research in multimodal search, and see your innovations directly impact millions of customers. If you're passionate about multimodal search and want to shape the future of how machines understand and retrieve information across different modalities, we want to hear from you.
Our team values research excellence and encourages publishing in top-tier conferences while maintaining a strong focus on practical applications that benefit real users.
Key job responsibilities
- As an Applied Scientist, you will leverage your technical expertise and experience to demonstrate leadership in tackling large complex problems, setting the direction and collaborating with applied scientists and engineers to develop novel algorithms and modeling techniques to enable timely, relevant and delightful search experiences.
- Develop state-of-the-art multimodal search technology, including training novel retrieval and ranking models for images/videos, scaling models and optimizing performance, partnering with engineering to deploy and debug model performance in production, and building and scaling quality training data sets.
- Leverage Amazon's data and computing resources to accelerate advances in the state of the art in multimodal learning and information retrieval.
- Work backwards from customer needs and use that information to make trade-offs between different modeling approaches
- Collaborate with software engineering teams to integrate successful experimental results into complex Amazon production systems
- Report results to technical and business audiences in a manner that is statistically rigorous and compellingly relevant, exemplifying good scientific practice in a business environment
- Drive best practices, helping to set high scientific and engineering standards on the team
- Promote the culture of experimentation and applied science at Amazon
BASIC QUALIFICATIONS
- 1+ 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
- PhD in Computer Science/Engineering, Machine Learning, or related field with specialties in information retrieval, recommendation system, or multimodal learning.
- Hands on experience with Visual LLMs
- Publications at peer-reviewed NLP/ML conferences (e.g. ACL, EMNLP, NAACL, NeurIPS, ICLR, ICML, AAAI, CVPR)
- Scientific thinking and the ability to invent, a track record of thought leadership and contributions that have advanced the field
- Experience with distributed systems, web services, or large-scale data processing.
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.
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.
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 https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you're applying in isn't 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 $136,000/year in our lowest geographic market up to $223,400/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.
We're seeking a creative problem-solver who's excited about architecting novel deep learning solutions for multimodal search and retrieval. You'll work on advancing the state-of-the-art in vision-language models and multimodal embeddings, while developing efficient and scalable algorithms for cross-modal retrieval. Your role will involve creating innovative solutions for multimodal ranking and relevance, ultimately building the next generation of multimodal search systems that can understand and process information the way humans do.
You'll collaborate with a talented team of researchers and engineers, contribute to research in multimodal search, and see your innovations directly impact millions of customers. If you're passionate about multimodal search and want to shape the future of how machines understand and retrieve information across different modalities, we want to hear from you.
Our team values research excellence and encourages publishing in top-tier conferences while maintaining a strong focus on practical applications that benefit real users.
Key job responsibilities
- As an Applied Scientist, you will leverage your technical expertise and experience to demonstrate leadership in tackling large complex problems, setting the direction and collaborating with applied scientists and engineers to develop novel algorithms and modeling techniques to enable timely, relevant and delightful search experiences.
- Develop state-of-the-art multimodal search technology, including training novel retrieval and ranking models for images/videos, scaling models and optimizing performance, partnering with engineering to deploy and debug model performance in production, and building and scaling quality training data sets.
- Leverage Amazon's data and computing resources to accelerate advances in the state of the art in multimodal learning and information retrieval.
- Work backwards from customer needs and use that information to make trade-offs between different modeling approaches
- Collaborate with software engineering teams to integrate successful experimental results into complex Amazon production systems
- Report results to technical and business audiences in a manner that is statistically rigorous and compellingly relevant, exemplifying good scientific practice in a business environment
- Drive best practices, helping to set high scientific and engineering standards on the team
- Promote the culture of experimentation and applied science at Amazon
BASIC QUALIFICATIONS
- 1+ 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
- PhD in Computer Science/Engineering, Machine Learning, or related field with specialties in information retrieval, recommendation system, or multimodal learning.
- Hands on experience with Visual LLMs
- Publications at peer-reviewed NLP/ML conferences (e.g. ACL, EMNLP, NAACL, NeurIPS, ICLR, ICML, AAAI, CVPR)
- Scientific thinking and the ability to invent, a track record of thought leadership and contributions that have advanced the field
- Experience with distributed systems, web services, or large-scale data processing.
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.
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.
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 https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you're applying in isn't 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 $136,000/year in our lowest geographic market up to $223,400/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.