Applied Scientist II, Generative AI Innovation Center

Machine learning (ML) has been vital to Amazon since its early stages. We have led the way in areas such as recommendation engines, product search, eCommerce fraud detection, and large-scale optimization of fulfillment center operations. The Generative AI team supports AWS customers in accelerating the use of Generative AI to address business and operational challenges, and fostering innovation within their organizations. As an applied scientist, your expertise lies in designing and developing advanced ML models to address a range of challenges and opportunities. You will work with terabytes of textual, image, and other types of data to address real-world issues. You will design and run experiments, investigate new algorithms, and explore new ways of optimizing risk, profitability, and customer experience. We are seeking talented scientists capable of applying ML algorithms and state-of-the-art deep learning (DL) and reinforcement learning approaches to various fields such as drug discovery, customer segmentation, fraud prevention, capacity planning, predictive maintenance, pricing optimization, call center analytics, player pose estimation, event detection, and virtual assistants, among others. Key Job Responsibilities The primary duties of this role include the following: Design, develop, and evaluate innovative ML models to address diverse challenges and opportunities across various sectors. Engage directly with customers to understand their business issues and assist them in defining and implementing scalable Generative AI solutions to solve their problems. Collaborate closely with account teams, research scientist teams, and product engineering teams to promote model implementations and new solutions. Inclusive Team Culture Here at AWS, we appreciate our differences. We are dedicated to continuing to foster our culture of inclusion. We have ten employee-led affinity groups that encompass 40,000 employees across more than 190 chapters worldwide. We offer innovative benefits and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Work/Life Balance Our team values work-life balance highly. It's not about the number of hours spent at home or work, but the energy flow established, enriching both aspects of your life. We believe the right balance between your personal and professional life is crucial for lifelong happiness and fulfillment. We offer flexible working hours and encourage you to establish your unique balance between your work and personal lives. Mentorship & Career Growth Our team is committed to supporting new members. We have a diverse mix of experience levels and tenure, fostering a culture that welcomes knowledge sharing and mentorship. Our senior members delight in one-on-one mentoring and thorough, though constructive, code reviews. We care about your career growth and aim to assign projects based on what will help each team member grow into a better-rounded engineer and take on more advanced tasks in the future. We are open to hiring candidates who can work out of one of the following locations: Santa Clara, CA, USA Basic Qualifications 3+ years of experience building models for business applications PhD, or a Master's degree and 4+ years of experience in CS, CE, ML or a related field Experience in patents or publications at top-tier peer-reviewed conferences or journals Experience programming in Java, C++, Python or a similar language Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing Experience with deep learning methods and machine learning Preferred Qualifications Experience in professional software development PhD degree in computer science, engineering, mathematics, operations research, or in a highly quantitative field Practical experience solving complex issues in an applied environment Hands-on experience building models with deep learning frameworks like MXNet, TensorFlow, or PyTorch Strong communication skills, attention to detail, and ability to communicate complex mathematical concepts and considerations to non-experts Comfort working in a fast-paced, collaborative, dynamic work environment Scientific thinking and the ability to invent, a record of thought leadership, and contributions that have advanced the field Amazon is committed to fostering 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 any other legally protected status. Individuals with disabilities who would like to request an accommodation can visit https://www.amazon.jobs/en/disability/us. Our compensation reflects labor cost across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographic market up to $222,200/year in our highest geographic market. Pay depends on various factors, including market location and job-related knowledge, skills, and experience. Amazon is a total compensation company. Depending 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. Candidates should apply via our internal or external career site.