Mobile Engineer, Beauty Tech

at  Amazoncom Services LLC A57

• 5+ years of non-internship professional software development experience
• 5+ years of programming with at least one software programming language experience
• 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
• Experience as a mentor, tech lead or leading an engineering team
• 4+ years of application development experience with Android/iOS
• 4+ years of experience with Mobile frameworks
  Description
  Are you passionate about using the latest advances in technology to redefine the beauty shopping experience? Look no further than Amazon’s Beauty Tech team! We are reinventing the way customers discover, shop, and engage with beauty products online. Powered by cutting-edge machine learning, computer vision, and generative AI technologies, as well as beautiful, elevated, and visually appealing customer experiences, we are striving to build immersive and personalized experiences to provide the best-in-class experience for our Beauty customers.
  Our Vision
  Beauty Tech’s (BT) vision is to make Amazon the world’s most trusted Beauty destination by elevating the beauty shopping experience to make it personalized, inspiring, and inclusive.
  Our Tech
  If you are an SDE looking to work on cutting-edge technologies to solve difficult customer problems, some of the exciting work we are doing includes leveraging machine learning and generative AI to power beauty solutions. Over the past 3 years, we have been at the forefront of research, development, and productization of solutions using computer vision, traditional ML, and generative AI to solve unique customer problems. We have deployed beauty virtual try-on solutions in production today, utilizing multimodal ML models.
  Key job responsibilities

We are looking for talented and innovation-driven mobile engineers who are passionate about raising the bar on building immersive and elevated customer experiences. You will have an opportunity to revolutionize the customer shopping experience across the world’s most extensive catalog of beauty products. You will be directly responsible for:

• Design and develop Mobile applications that integrate generative AI models. This includes building and maintaining scalable and efficient software that can run CV/ML models on Mobile devices.
• Optimize AI models for on-device deployment, focusing on reducing latency and memory usage while maintaining model performance. This involves techniques such as quantization, pruning, and knowledge distillation.
• Integrate and utilize edge ML frameworks to deploy AI models on Mobile devices. This includes adapting models to these frameworks and ensuring they can run efficiently in a mobile environment.
• Benchmark model performance on various devices to ensure optimal compatibility and efficiency. Address issues related to different hardware capabilities across Android and iOS devices.
• Collaborate with cross-functional teams including product management, design, and QA to ensure that AI features align with business objectives and customer needs.
• Work closely with applied science teams to understand the requirements and limitations of AI models and translate these into practical, deployable mobile solutions.

We are open to hiring candidates to work out of one of the following locations:

Seattle, WA, USA

• 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
• Master’s degree or PhD in computer science, computer engineering, or equivalent
• Experience in mobile design patterns (MVVM, MVI, VIPER), building mobile frameworks / SDKs, building custom UX widgets and optimizing apps for performance (Instruments)
• Experience writing testable code and automating test regressions
• Experience with multi-module application in a large distributed team environment
• Knowledge of professional software engineering practices including coding standards, code reviews, source control management, build processes, testing and operations
• Experience developing, releasing, and maintaining Mobile apps
• Experience deploying ML frameworks like TensorFlow Lite, PyTorch Mobile, or ONNX on Mobile devices.
• Experience with REST architecture for web services
• Experience communicating technical problems to both technical and business audiences verbally and in writing

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 $134,500/year in our lowest geographic market up to $261,500/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

• Design and develop Mobile applications that integrate generative AI models. This includes building and maintaining scalable and efficient software that can run CV/ML models on Mobile devices.
• Optimize AI models for on-device deployment, focusing on reducing latency and memory usage while maintaining model performance. This involves techniques such as quantization, pruning, and knowledge distillation.
• Integrate and utilize edge ML frameworks to deploy AI models on Mobile devices. This includes adapting models to these frameworks and ensuring they can run efficiently in a mobile environment.
• Benchmark model performance on various devices to ensure optimal compatibility and efficiency. Address issues related to different hardware capabilities across Android and iOS devices.
• Collaborate with cross-functional teams including product management, design, and QA to ensure that AI features align with business objectives and customer needs.
• Work closely with applied science teams to understand the requirements and limitations of AI models and translate these into practical, deployable mobile solutions