Careers

Amazon is looking for a passionate, talented, and inventive Scientist with a strong machine learning background to help build industry-leading Speech and Language technology. Our mission is to push the envelope in Automatic Speech Recognition (ASR), Natural Language Understanding (NLU), and Audio Signal Processing, in order to provide the best-possible experience for our customers. As a Speech and Language Scientist, you will work with talented peers to develop novel algorithms and modeling techniques to advance the state of the art in spoken language understanding. Your work will directly impact our customers in the form of products and services that make use of speech and language technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in spoken language understanding. We are hiring in the area of speech recognition (ASR).

Amazon is looking for a passionate, talented, and inventive Scientist with a strong machine learning background to help build industry-leading Speech and Language technology. Our mission is to push the envelope in Automatic Speech Recognition (ASR), Natural Language Understanding (NLU), and Audio Signal Processing, in order to provide the best-possible experience for our customers. As a Speech and Language Scientist, you will work with talented peers to develop novel algorithms and modeling techniques to advance the state of the art in spoken language understanding. Your work will directly impact our customers in the form of products and services that make use of speech and language technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in spoken language understanding. We are hiring in the area of speech recognition (ASR).

Stores Economics and Science (SEAS) is an interdisciplinary science and engineering team in Amazon's Stores organization with a peak-jumping mission: we apply expertise in science and engineering to move from local to global optima in methods, models, and software. We pursue this mission by leveraging frontier science; collaborating with partner teams; and learning from the tools, experience, and perspective of others. We scale by solving problems, first in the small to prove concepts, and then in the large by building scalable solutions. We also help other teams within Amazon scale by hiring and developing the best and embedding them in other business units. In 2024, we are focused on economics and science in areas related to (1) improving delivery speed and lowering cost-to-serve, (2) seller fees and incentives, and (3) emerging machine learning using LLMs. We also have some ongoing and highly leveraged collaborations that help partner teams inside Amazon short-circuit months of R&D or otherwise look around corners. We are looking for a seasoned Applied Science leader to build and deliver cutting-edge science and engineering solutions to improve our Stores business. In this role, you will lead a team of scientists and engineers with backgrounds in machine learning, NLP, IR, statistics, and economics to identify bottlenecks in our business, conceive new ideas to overcome those challenges, and deploy scientific solutions in partnership with product teams. Your responsibilities include developing the scientific models, benchmarks, and services. Graduate education and hands-on experience in machine learning, optimization, causal inference, Bayesian statistics, deep learning, or other quantitative scientific fields is a must. To be successful in this role, you should be a quick learner and comfortable with a high degree of ambiguity. Key job responsibilities Knowledge of causal inference and forecasting models are preferred. Practical knowledge of how we can leverage Transformers, LLMs, or other deep learning techniques for a variety of applications is a must.

Do you want to join an innovative team of scientists who use deep learning, natural language processing, large language models to help Amazon provide the best seller experience across the entire Seller life cycle, including recruitment, growth, support and provide the best customer and seller experience by automatically mitigating risk? Do you want to build advanced algorithmic systems that help manage the trust and safety of millions of customer interactions every day? Are you excited by the prospect of analyzing and modeling terabytes of data and creating state-of-the-art algorithms to solve real world problems? Are you excited by the opportunity to leverage GenAI and innovate on top of the state-of-the-art large language models to improve customer and seller experience? Do you like to build end-to-end business solutions and directly impact the profitability of the company? Do you like to innovate and simplify processes? If yes, then you may be a great fit to join the Machine Learning Accelerator team in the Amazon Selling Partner Services (SPS) group. Key job responsibilities The scope of an Applied Scientist III in the Selling Partner Services (SPS) Machine Learning Accelerator (MLA) team is to research and prototype Machine Learning applications that solve strategic business problems across SPS domains. Additionally, the scientist collaborates with engineers and business partners to design and implement solutions at scale when they are determined to be of broad benefit to SPS organizations. They develop large-scale solutions for high impact projects, introduce tools and other techniques that can be used to solve problems from various perspectives, and show depth and competence in more than one area. They influence the team’s technical strategy by making insightful contributions to the team’s priorities, approach and planning. They develop and introduce tools and practices that streamline the work of the team, and they mentor junior team members and participate in hiring.

As a Principal Scientist within the Artificial General Intelligence (AGI) organization, you are a trusted part of the technical leadership. You bring business and industry context to science and technology decisions. You set the standard for scientific excellence and make decisions that affect the way we build and integrate algorithms. You solicit differing views across the organization and are willing to change your mind as you learn more. Your artifacts are exemplary and often used as reference across organization. You are a hands-on scientific leader. Your solutions are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility. You tackle intrinsically hard problems, acquiring expertise as needed. You decompose complex problems into straightforward solutions. You amplify your impact by leading scientific reviews within your organization or at your location. You scrutinize and review experimental design, modeling, verification and other research procedures. You probe assumptions, illuminate pitfalls, and foster shared understanding. You align teams toward coherent strategies. You educate, keeping the scientific community up to date on advanced techniques, state of the art approaches, the latest technologies, and trends. You help managers guide the career growth of other scientists by mentoring and play a significant role in hiring and developing scientists and leads. You will play a critical role in driving the development of Generative AI (GenAI) technologies that can handle Amazon-scale use cases and have a significant impact on our customers' experiences. Key job responsibilities You will be responsible for defining key research directions, adopting or inventing new machine learning techniques, conducting rigorous experiments, publishing results, and ensuring that research is translated into practice. You will develop long-term strategies, persuade teams to adopt those strategies, propose goals and deliver on them. You will also participate in organizational planning, hiring, mentorship and leadership development. You will be technically fearless and with a passion for building scalable science and engineering solutions. You will serve as a key scientific resource in full-cycle development (conception, design, implementation, testing to documentation, delivery, and maintenance). About the team The AGI team has a mission to push the envelope with multimodal LLMs and Gen AI in Computer Vision, in order to provide the best-possible experience for our customers.

The Postdoc for this role will research safety and efficiency aspects of generative AI for industries. From the safety perspective, the postdoc will research and present (internally and externally) a novel contribution to hallucination reduction, model/data/prompt safety or privacy-preserving training or fine-tuning methods with direct applications in one of our core industry segments. From the efficiency perspective, the postdoc will research and present a novel contribution to training, fine-tuning or operationalization methods that reduce cost, memory or carbon footprint of foundation models with a demonstration of its application in one of our core industry segments. Key job responsibilities This is a unique opportunity for a Postdoc to spearhead the effort to address safety and efficiency challenges behind adopting generative AI for Amazon's funded and ongoing industry product initiatives. This research will feed directly into Amazon's generative AI product strategies and features with industry customers and AIP segments. About the team The AWS Industry Products (AIP) team directly collaborates with strategic customers to build new, industry-specific products that directly impact and transform industries at AWS scale. We are a team of innovators that tackle difficult problems, and build products through fast iteration in a start-up like environment. AIP SCIFI team was formed to empower our customers to make better data-driven decisions by leveraging data science techniques such as ML and optimization.

Amazon is looking for talented Postdoctoral Scientists to join our Forward Looking Initiatives & Technology Enablers (FLITE) Team for a one-year, full-time research position. The Forward Looking Initiatives & Technology Enablers (FLITE) Team. FLITE’s charter is to enable Amazon Robotics Manipulation Organization to innovate on advanced technology development. The research work for this position will explore generalization of grasp policies in simulation and on novel hardware platforms. The Postdoc will research, propose, and develop policies by leveraging the state-of-the-art visuomotor polices, data-efficient reinforcement learning methods, and foundation models for robotic perception and manipulation. The candidate will prototype algorithms in simulation and then deploy promising solutions to real and novel hardware. They will provide direction on where we should be focusing our efforts in this rapidly developing field and innovate and iterate on deep learning solutions for robotic manipulation. Key job responsibilities • Work closely with a senior science advisor, collaborate with other scientists and engineers, and be part of Amazon’s vibrant and diverse global science community. • Publish your innovation in top-tier academic venues and hone your presentation skills. • Be inspired by challenges and opportunities to invent cutting-edge techniques in your area(s) of expertise.

Amazon is looking for a talented Postdoctoral Scientist to join its AI Research on foundation models, large-scale representation learning, and distributed learning methods and systems for a one-year, full-time research position. At Amazon, you will invent, implement, and deploy state of the art machine learning algorithms and systems. You will build prototypes and innovate on new representation learning solutions. You will interact closely with our customers and with the academic and research communities. You will be at the heart of a growing and exciting focus area and work with other acclaimed engineers and world famous scientists. Large-scale foundation models have been the powerhouse in many of the recent advancements in computer vision, natural language processing, automatic speech recognition, recommendation systems, and time series modeling. Developing such models requires not only skillful modeling in individual modalities, but also understanding of how to synergistically combine them, and how to scale the modeling methods to learn with huge models and on large datasets. Join us to work as an integral part of a team that has diverse experiences in this space. We actively work on these areas: * Hardware-informed efficient model architecture, training objective and curriculum design * Distributed training, accelerated optimization methods * Continual learning, multi-task/meta learning * Reasoning, interactive learning, reinforcement learning * Robustness, privacy, model watermarking * Model compression, distillation, pruning, sparsification, quantization In this role, you will have the opportunity to: - Leverage machine learning models and advanced statistical techniques to extract valuable insights from historical data and comparable item information. - Tackle data scarcity challenges by developing innovative approaches to maximize the utility of available data sources. - Collaborate with cross-functional teams to develop and deploy production-ready solutions. - Participate in research activities, including publishing papers, attending conferences, and collaborating with academic institutions to advance the state-of-the-art in relevant fields. Key job responsibilities In this role you will: • Work closely with a senior science advisor, collaborate with other scientists and engineers, and be part of Amazon’s vibrant and diverse global science community. • Publish your innovation in top-tier academic venues and hone your presentation skills. • Be inspired by challenges and opportunities to invent cutting-edge techniques in your area(s) of expertise.