Job
Description
Have you ever wondered how Amazon launches and maintains a consistent customer experience across hundreds of countries and languages it serves its customersAre you passionate about data and mathematics, and hope to impact the experience of millions of customersAre you obsessed with designing simple algorithmic solutions to very challenging problemsIf so, we look forward to hearing from you!
At Amazon, we strive to be Earths most customer-centric company, where both internal and external customers can find and discover anything they want in their own language of preference. Our Translations Services (TS) team plays a pivotal role in expanding the reach of our marketplace worldwide and enables thousands of developers and other stakeholders (Product Managers, Program Managers, Linguists) in developing locale specific solutions. Amazon Translations Services (TS) is seeking a Senior Applied Scientist to be based in our Hyderabad office. As a key member of the Science and Engineering team of TS, this person will be responsible for designing algorithmic solutions based on data and mathematics for translating billions of words annually across 130+ and expanding set of locales. The successful applicant will ensure that there is minimal human touch involved in any language translation and accurate translated text is available to our worldwide customers in a streamlined and optimized manner. With access to vast amounts of data, technology, and a diverse community of talented individuals, you will have the opportunity to make a meaningful impact on the way customers and stakeholders engage with Amazon and our platform worldwide. Together, we will drive innovation, solve complex problems, and shape the future of e-commerce. Lead and innovate in applying advanced NLP and LLM techniques to solve complex language translation challenges in e-commerce, driving product-level improvements for our international marketplaces. Drive innovation on Image and Video translation. Architect and implement novel, scalable machine learning solutions that enhance translation quality evaluation and improve translation pipeline efficiency across multiple teams and systems. Spearhead cross-functional collaborations to define strategic project requirements, establish organization-wide success metrics, and deliver high-impact solutions aligning with broader business objectives. Drive comprehensive data analysis to uncover non-obvious insights in multilingual data, relaying findings into actionable strategies that influence product roadmaps and capabilities for language technologies. Pioneer and implement modeling techniques for machine translation quality assessment and pipeline optimization, leading the teams scientific agenda. Invent new methodologies when existing approaches fall short, advancing the state-of-the-art. Serve as a recognized expert in LLM applications for e-commerce translation, communicating complex concepts to diverse stakeholders including senior leadership. Influence organization-wide adoption of innovative approaches in language translation technologies. Actively mentor team members, elevating scientific capabilities and fostering a culture of innovation and rigorous inquiry in machine translation and evaluation. About the team We are a start-up mindset team. As the long-term technical strategy is still taking shape, there is a lot of opportunity for this fresh Science team to innovate by leveraging Gen AI technoligies to build scalable solutions from scratch. Our Vision: Language will not stand in the way of anyone on earth using Amazon products and services. Our Mission: We are the enablers and guardians of translation for Amazons customers. We do this by offering hands-off-the-wheel service to all Amazon teams, optimizing translation quality and speed at the lowest cost possible. 3+ years of building machine learning models for business application experience PhD, or Masters degree and 5+ years of applied research experience Experience programming in Java, C++, Python or related language Experience with neural deep learning methods and machine learning Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc. Experience with large scale distributed systems such as Hadoop, Spark etc.
