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Machine learning

Developing algorithms and statistical models that computer systems use to perform tasks without explicit instructions, relying on patterns and inference instead.
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  • A likelihood ratio-based domain adaptation method for end-to-end models
    Chhavi Choudhury, Ankur Gandhe, Xiaohan Ding, Ivan Bulyko
    ICASSP 2022
    2022
    End-to-end (E2E) automatic speech recognition models like Recurrent Neural Networks Transducer (RNN-T) are becoming a popular choice for streaming ASR applications like voice assistants. While E2E models are very effective at learning representation of the training data they are trained on, their accuracy on unseen domains remains a challenging problem. Additionally, these models require paired audio and
    Machine learning
  • DocBed: A multi-stage OCR solution for documents with complex layouts
    Wenzhen Zhu, Negin Sokhandan, Guang Yang, Sujitha Martin, Suchitra Sathyanarayana
    AAAI 2022
    2022
    Digitization of newspapers is of interest for many reasons including preservation of history, accessibility and search ability, etc. While digitization of documents such as scientific articles and magazines is prevalent in literature, one of the main challenges for digitization of newspaper lies in its complex layout (e.g. articles spanning multiple columns, text interrupted by images) analysis, which is
    Computer vision
  • PECOS: Prediction for enormous and correlated output spaces
    Hsiang-Fu Yu, Kai Zhong, Jiong Zhang, Wei-Cheng Chang, Inderjit S. Dhillon
    Journal of Machine Learning Research
    2022
    Many large-scale applications amount to finding relevant results from an enormous output space of potential candidates. For example, finding the best matching product from a large catalog or suggesting related search phrases on a search engine. The size of the output space for these problems can range from millions to billions, and can even be infinite in some applications. Moreover, training data is often
    Machine learning
  • Prediction of tuberculosis using an automated machine learning platform for models trained on synthetic data
    Hooman H. Rashidi, Imran H. Khan, Luke T. Dang, Samer Albahra, Ujjwal Ratan, Nihir Chadderwala, Wilson To, Prathima Srinivas, Jeffery Wajda, Nam K. Tran
    Journal of Pathology Informatics
    2022
    High-quality medical data is critical to the development and implementation of machine learning (ML) algorithms in healthcare; however, security, and privacy concerns continue to limit access. We sought to determine the utility of “synthetic data” in training ML algorithms for the detection of tuberculosis (TB) from inflammatory biomarker profiles. A retrospective dataset (A) comprised of 278 patients was
    Machine learning
  • Subjective influence of camera-gaze angular offset
    Jan Holub, Scott Isabelle, Adéla Krylová, Hakob Avetisyan
    IEEE Access
    2022
    The study aimed to evaluate the difficulty in maintaining eye contact during a teleconference for different camera-gaze angular offsets. Videoconferencing systems may compromise the eye contact between participants due to imperfect angular alignment between the center of the screen and the camera. During a teleconference, difficulty maintaining eye contact may be perceived as uncomfortable or unsatisfying
    Machine learning
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Applied Scientist - Perception (SLAM/VIO), Fauna
US, NY, New York
We are seeking an Applied Scientist to develop and optimize Visual Inertial Odometry (VIO) and sensor fusion systems for our intelligent robots. In this role, you will design, implement, and deploy state estimation and tracking algorithms that enable robots to understand their position and motion in real time, even in challenging and dynamic environments. You will own the full pipeline from algorithm development through embedded deployment, ensuring that perception systems run efficiently on resource-constrained robotic hardware. You will also leverage modern machine learning approaches to push the boundaries of classical perception methods, combining learned representations with geometric techniques to achieve robust, real-time performance. This is a deeply hands-on role. You will work directly with sensors, hardware, and real-world data, while prototyping, testing, and iterating in physical environments. The ideal candidate has strong foundations in VIO and sensor fusion, practical experience optimizing algorithms for embedded platforms, and familiarity with how modern deep learning is transforming perception. Key job responsibilities - Design and implement Visual Inertial Odometry algorithms for robust real-time state estimation on robotic platforms like Sprout - Develop multi-sensor fusion pipelines integrating cameras, IMUs, and other sensing modalities for accurate pose tracking - Optimize perception and tracking algorithms for deployment on embedded hardware (e.g., ARM, GPU-accelerated edge devices) under strict latency and power constraints - Apply modern ML-based perception techniques (learned features, depth estimation, neural odometry) to complement and improve classical geometric approaches - Build and maintain calibration, evaluation, and benchmarking infrastructure for perception systems - Collaborate with hardware, controls, and navigation teams to integrate perception outputs into the robot’s autonomy stack - Lead technical projects from research prototyping through production deployment
Sr. Research Scientist, Pricing Science
US, WA, Seattle
Amazon's Worldwide Pricing & Promotions organization is seeking a talented, hands-on Research Scientist to join the Pricing and Promotion Optimization Science (P2OS) team — the optimization "application layer" within Amazon's Pricing Sciences organization. Amazon adjusts prices on hundreds of millions of products daily across a global marketplace; P2OS is the team that makes those prices optimal. P2OS is a small, specialized unit with an outsized charter: develop and maintain the models that determine optimal prices and promotions across Amazon's catalog and merchant programs. We own the full optimization stack — from price prediction to promotion targeting to competitiveness guardrails — and we measure success in terms of accretive Gross Contribution and Customer Pricing Perception (GCCP). Our work spans Retail Core, Amazon Business, Fresh, Grocery, and international marketplaces, and we are continually investing in more extensible, generalizable science foundations to keep pace with a growing and evolving business. We are looking for an innovative, organized, and customer-focused scientist with exceptional machine learning and predictive modeling skills, causal and experimental evaluation experience, and the entrepreneurial spirit to apply state-of-the-art methods to some of the most impactful pricing problems in e-commerce. You should be comfortable with ambiguity, motivated by measurable business impact, and excited by the opportunity to work at Amazon-scale. Key job responsibilities * Innovate and build. Design, develop, and deploy machine learning models that set optimal prices and promotions across Amazon's global catalog. Own models end-to-end — from problem formulation and data analysis through offline evaluation, A/B testing, and production launch. * Build a generalizable science foundation. Develop models and evaluation frameworks designed to scale across merchant programs, product categories, and marketplaces — enabling cross-learning and reducing the time and cost of applying science to new business contexts. * Build and evolve optimization systems. Design and improve optimization systems — including reinforcement learning and multi-objective optimization approaches — that automate price and promotion decisions at scale across millions of products. * Apply generative AI and foundation models. Identify and pursue opportunities to leverage large language models, embeddings, and generative AI techniques in pricing science — from enriching product representations and extracting competitive signals from unstructured data, to building more capable and explainable pricing systems. * Experiment rigorously. Design and execute A/B tests and causal inference studies to measure the business and customer impact of pricing model changes. Translate findings into production-ready science improvements. * Stay at the frontier. Establish mechanisms to track the latest advances in reinforcement learning, causal ML, multi-objective optimization, generative AI, and demand modeling — and identify opportunities to apply them to Pricing & Promotions business problems. * See the big picture. Contribute to the long-term scientific vision for how Amazon sets competitive, perception-preserving prices — balancing profitability, customer trust, and marketplace health.
Sr. Applied Scientist, Special Projects
US, WA, Seattle
Innovators wanted! Are you an entrepreneur? A builder? A dreamer? This role is part of an Amazon Special Projects team that takes the company’s Think Big leadership principle to the limits. If you’re interested in innovating at scale to address big challenges in the world, this is the team for you. As an Applied Scientist on our team, you will focus on building state-of-the-art ML models for biology. Our team rewards curiosity while maintaining a laser-focus in bringing products to market. Competitive candidates are responsive, flexible, and able to succeed within an open, collaborative, entrepreneurial, startup-like environment. At the forefront of both academic and applied research in this product area, you have the opportunity to work together with a diverse and talented team of scientists, engineers, and product managers and collaborate with other teams. Key job responsibilities - Build, adapt and evaluate ML models for life sciences applications - Collaborate with a cross-functional team of ML scientists, biologists, software engineers and product managers
Principal Applied Scientist, Automated Reasoning Group
US, WA, Seattle
Applied Scientists in AWS Automated Reasoning are dedicated to making AWS the best computing service in the world for customers who require advanced and rigorous solutions for automated reasoning, privacy, and sovereignty. Key job responsibilities - Solve large or significantly complex problems that require deep knowledge and understanding of your domain and scientific innovation. - Own strategic problem solving, and take the lead on the design, implementation, and delivery for solutions that have a long-term quantifiable impact. - Provide cross-organizational technical influence, increasing productivity and effectiveness by sharing your deep knowledge and experience. - Develop strategic plans to identify fundamentally new solutions for business problems. - Assist in the career development of others, actively mentoring individuals and the community on advanced technical issues.
Economist III - AMZ9898444
US, MA, Boston
MULTIPLE POSITIONS AVAILABLE Employer: AMAZON.COM SERVICES LLC Offered Position: Economist III Job Location: Boston, Massachusetts Job Number: AMZ9898444 Position Responsibilities: Mentor and guide the applied scientists and economists in our organization and hold us to a high standard of technical rigor and excellence in science. Design and lead roadmaps for complex science projects to help SP have a delightful selling experience while creating long term value for our shoppers. Work with our engineering partners and draw upon your experience to meet latency and other system constraints. Identify untapped, high-risk technical and scientific directions, and simulate new research directions that you will drive to completion and deliver. Be responsible for communicating our science innovations to the broader internal & external scientific community. Position Requirements: Ph.D. or foreign equivalent degree in Economics or a related field and two years of research or work experience in the job offered or a related occupation. Must have two years of research or work experience in the following skill(s): 1) experience in econometrics including experience with program evaluation, forecasting, time series, panel data, or high dimensional problems; 2) experience with economic theory and quantitative methods; and 3) coding in a scripting language such as R, Python, or similar. Amazon.com is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation. 40 hours / week, 8:00am-5:00pm, Salary Range $159,200/year to $215,300/year. 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, visit: https://www.aboutamazon.com/workplace/employee-benefits.#0000
Applied Scientist, Navigation
US, CA, San Francisco
Amazon is on a mission to redefine the future of automation — and we're looking for exceptional talent to help lead the way. We are building the next generation of advanced robotic systems that seamlessly blend cutting-edge AI, sophisticated control systems, and novel mechanical design to create adaptable, intelligent automation solutions capable of operating safely alongside humans in dynamic, real-world environments. At Amazon, we leverage the power of machine learning, artificial intelligence, and advanced robotics to solve some of the most complex operational challenges at a scale unlike anywhere else in the world. Our fleet of robots spans hundreds of facilities globally, working in sophisticated coordination to deliver on our promise of customer excellence — and we're just getting started. As a Sr. Scientist in Robot Navigation, you will be at the forefront of this transformation — architecting and delivering navigation systems that are intelligent, safe, and scalable. You will bring deep expertise in learning-based planning and control, a strong understanding of foundation models and their application to embodied agents, and as well as have in-depth understanding of control-theoretic approaches such as model predictive control (MPC)-based trajectory planning. You will develop navigation solutions that seamlessly blend data-driven intelligence with principled control-theoretic guarantees. Our vision is bold: to build navigation systems that allow robots to move fluidly and safely through dynamic environments — understanding context, anticipating change, and adapting in real time. You will lead research that bridges the gap between cutting-edge academic advances and production grade deployment, collaborating with world-class teams pushing the boundaries of robotic autonomy, manipulation, and human-robot interaction. Join us in building the next generation of intelligent navigation systems that will define the future of autonomous robotics at scale. Key job responsibilities - Design, develop, and deploy perception algorithms for robotics systems, including object detection, segmentation, tracking, depth estimation, and scene understanding - Lead research initiatives in computer vision, sensor fusion and 3D perception - Collaborate with cross-functional teams including robotics engineers, software engineers, and product managers to define and deliver perception capabilities - Drive end-to-end ownership of ML models — from data collection and labeling strategy to training, evaluation, and deployment - Mentor junior scientists and engineers; contribute to a culture of technical excellence - Define and track key metrics to measure perception system performance in real-world environments - Publish research findings in top-tier venues (CVPR, ICCV, ECCV, ICRA, NeurIPS, etc.) and contribute to patents A day in the life - Train ML models for deployment in simulation and real-world robots, identify and document their limitations post-deployment - Drive technical discussions within your team and with key stakeholders to develop innovative solutions to address identified limitations - Actively contribute to brainstorming sessions on adjacent topics, bringing fresh perspectives that help peers grow and succeed — and in doing so, build lasting trust across the team - Mentor team members while maintaining significant hands-on contribution to technical solutions About the team Our team is a group is a diverse group of scientists and engineers passionate about building intelligent machines. We value curiosity, rigor, and a bias for action. We believe in learning from failure and iterating quickly toward solutions that matter.
Economist II, GMAC Economics
GB, London
Are you excited about using econometrics, experimentation, and machine learning to impact real-world business decisions? We are looking for an Economist II to work on challenging problems at the intersection of causal inference and machine learning for Prime Video Ads. You will design experiments, build econometric and ML models, and translate findings into decisions that shape how millions of customers experience advertising on Prime Video. If you have a deeply quantitative approach to problem-solving, enjoy building and implementing models end-to-end, and want to work on problems where rigorous economics meets production-scale ML, we want to talk to you. Key job responsibilities - Design, execute, and analyze experiments to measure the impact of ad policies on customer behavior and business outcomes - Develop causal inference models (experimental and observational) to estimate short- and long-term effects of strategic initiatives - Collaborate with scientists, engineers, and product teams to deliver measurable business impact - Influence business leaders based on empirical findings
Applied Scientist, AWS Automated Reasoning
US, MA, Boston
Applied Scientists in AWS Automated Reasoning are dedicated to making AWS the best computing service in the world for customers who require advanced and rigorous solutions for automated reasoning, privacy, and sovereignty. Key job responsibilities The successful candidate will: - Solve large or significantly complex problems that require deep knowledge and understanding of your domain and scientific innovation. - Own strategic problem solving, and take the lead on the design, implementation, and delivery for solutions that have a long-term quantifiable impact. - Provide cross-organizational technical influence, increasing productivity and effectiveness by sharing your deep knowledge and experience. - Develop strategic plans to identify fundamentally new solutions for business problems. - Assist in the career development of others, actively mentoring individuals and the community on advanced technical issues. A day in the life This is a unique and rare opportunity to get in early on a fast-growing segment of AWS and help shape the technology, product and the business. You will have a chance to utilize your deep technical experience within a fast moving, start-up environment and make a large business and customer impact. About the team Diverse Experiences Amazon Automated Reasoning values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying. Why Amazon Automated Reasoning? At Amazon, automated reasoning is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for automated reasoning across all of Amazon's products and services. We offer talented automated reasoning professionals the chance to accelerate their careers with opportunities to build experience in a wide variety of areas including cloud, devices, retail, entertainment, healthcare, operations, and physical stores. Inclusive Team Culture In Amazon Automated Reasoning, it's in our nature to learn and be curious. Ongoing DEI events and learning experiences inspire us to continue learning and to embrace our uniqueness. Addressing the toughest automated reasoning challenges requires that we seek out and celebrate a diversity of ideas, perspectives, and voices. Training & Career Growth We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, training, and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there's nothing we can't achieve.
Applied Scientist, AWS Automated Reasoning
US, MA, Boston
Applied Scientists in AWS Automated Reasoning are dedicated to making AWS the best computing service in the world for customers who require advanced and rigorous solutions for automated reasoning, privacy, and sovereignty. Key job responsibilities The successful candidate will: - Solve large or significantly complex problems that require deep knowledge and understanding of your domain and scientific innovation. - Own strategic problem solving, and take the lead on the design, implementation, and delivery for solutions that have a long-term quantifiable impact. - Provide cross-organizational technical influence, increasing productivity and effectiveness by sharing your deep knowledge and experience. - Develop strategic plans to identify fundamentally new solutions for business problems. - Assist in the career development of others, actively mentoring individuals and the community on advanced technical issues. A day in the life This is a unique and rare opportunity to get in early on a fast-growing segment of AWS and help shape the technology, product and the business. You will have a chance to utilize your deep technical experience within a fast moving, start-up environment and make a large business and customer impact. About the team Diverse Experiences Amazon Automated Reasoning values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying. Why Amazon Automated Reasoning? At Amazon, automated reasoning is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for automated reasoning across all of Amazon's products and services. We offer talented automated reasoning professionals the chance to accelerate their careers with opportunities to build experience in a wide variety of areas including cloud, devices, retail, entertainment, healthcare, operations, and physical stores. Inclusive Team Culture In Amazon Automated Reasoning, it's in our nature to learn and be curious. Ongoing DEI events and learning experiences inspire us to continue learning and to embrace our uniqueness. Addressing the toughest automated reasoning challenges requires that we seek out and celebrate a diversity of ideas, perspectives, and voices. Training & Career Growth We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, training, and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there's nothing we can't achieve.
Applied Scientist, AWS Automated Reasoning
US, TX, Austin
Applied Scientists in AWS Automated Reasoning are dedicated to making AWS the best computing service in the world for customers who require advanced and rigorous solutions for automated reasoning, privacy, and sovereignty. Key job responsibilities The successful candidate will: - Solve large or significantly complex problems that require deep knowledge and understanding of your domain and scientific innovation. - Own strategic problem solving, and take the lead on the design, implementation, and delivery for solutions that have a long-term quantifiable impact. - Provide cross-organizational technical influence, increasing productivity and effectiveness by sharing your deep knowledge and experience. - Develop strategic plans to identify fundamentally new solutions for business problems. - Assist in the career development of others, actively mentoring individuals and the community on advanced technical issues. A day in the life This is a unique and rare opportunity to get in early on a fast-growing segment of AWS and help shape the technology, product and the business. You will have a chance to utilize your deep technical experience within a fast moving, start-up environment and make a large business and customer impact. About the team Diverse Experiences Amazon Automated Reasoning values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying. Why Amazon Automated Reasoning? At Amazon, automated reasoning is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for automated reasoning across all of Amazon's products and services. We offer talented automated reasoning professionals the chance to accelerate their careers with opportunities to build experience in a wide variety of areas including cloud, devices, retail, entertainment, healthcare, operations, and physical stores. Inclusive Team Culture In Amazon Automated Reasoning, it's in our nature to learn and be curious. Ongoing DEI events and learning experiences inspire us to continue learning and to embrace our uniqueness. Addressing the toughest automated reasoning challenges requires that we seek out and celebrate a diversity of ideas, perspectives, and voices. Training & Career Growth We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, training, and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there's nothing we can't achieve.
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