Amazon
Applied Scientist II, SPS Core Services
Amazon, Seattle, Washington, us, 98127
Job ID: 2632758 | Amazon.com Services LLCThe CATALST NLP Services team within the Selling Partner Services (SPS) Core Services organization is responsible for simplifying multi-lingual experiences for our customers. We build and leverage various AI services to eliminate language barriers at scale through Machine Translation for Amazon Customers and Sellers WW across 30+ programs within SPS and customers outside of SPS. We leverage state-of-the-art NLP solutions including Large Language Models, Machine Translation, Language Detection, and OCR to provide a full suite of content analysis capabilities. Our customers include Selling Partners, Buyers, Amazon Associates, Amazon Investigators, and various Science teams.In this role, you will be a key owner within our cross-disciplinary team that includes Product Managers, Software Engineers, and Applied Scientists and execute on our 3 Year Plan. You will pioneer new technologies in NLP, machine translation, and machine learning. You will have ownership of the end-to-end development of solutions to complex problems from design to implementation and you will play an integral role in strategic decision-making. You will also work closely with other stakeholders such as engineers, operations teams and product owners to build ML pipelines, platforms and solutions that solve business problems.Key job responsibilities
Participate in the design, development, evaluation, deployment and updating of automated and scalable machine learning models, with a focus on machine translation.Develop and/or apply statistics, NLP and machine learning experiments and methodologies to different applications.Work closely with Scientists and Software Engineers on experimentations, evaluation and implementation.Work closely with business partners to understand the goals and develop solutions to achieve such goals.We are open to hiring candidates to work out of one of the following locations: Seattle, WA, USA.BASIC QUALIFICATIONS
- 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 building machine learning models or developing algorithms for business application.PREFERRED QUALIFICATIONS
- Experience in building speech recognition, machine translation and natural language processing systems (e.g., commercial speech products or government speech projects).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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Participate in the design, development, evaluation, deployment and updating of automated and scalable machine learning models, with a focus on machine translation.Develop and/or apply statistics, NLP and machine learning experiments and methodologies to different applications.Work closely with Scientists and Software Engineers on experimentations, evaluation and implementation.Work closely with business partners to understand the goals and develop solutions to achieve such goals.We are open to hiring candidates to work out of one of the following locations: Seattle, WA, USA.BASIC QUALIFICATIONS
- 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 building machine learning models or developing algorithms for business application.PREFERRED QUALIFICATIONS
- Experience in building speech recognition, machine translation and natural language processing systems (e.g., commercial speech products or government speech projects).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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