Amazon Science celebrates Pi Day

Times Square display honors scientists, engineers, and mathematicians past, present, and future.

  1. Pi Day is an annual celebration of the mathematical constant π (pi), and is observed on March 14 since 3, 1, and 4 are the first three significant digits of π. Pi Day was first observed in 1988, and since then celebrations of the day often have involved eating pie, or holding various mathematical competitions.

    To mark Pi Day this year, Amazon Science utilized a Times Square billboard normally used by Amazon Music to honor scientists, engineers, and mathematicians past, present, and future.

    The billboard display ran from midnight to 8 a.m. and again — for 3 hours and 14 minutes — from 3:14 p.m. to 6:28 p.m. The display (which you can watch above) began by honoring Marie Curie, the first woman to be awarded a Nobel Prize in 1903 for her contributions to physics. It was Curie who once famously said, “Nothing in life is to be feared, it is only to be understood. Now is the time to understand more, so that we may fear less.”

    On Pi Day, we honored some of the scientific giants on whose shoulders we stand, feature a few key accomplishments achieved by Amazon’s researchers and engineers, and highlight some of our university collaborators who are developing the next generation of STEM talent who will help us understand our world more fully, so we may fear less.

    For, as Alan Turing once said, “We can only see a short distance ahead, but we can see plenty there that needs to be done.”

    Below are items highlighted on the Times Square billboard:

  2. Marie Curie — 21911

    Curie — the first and only person to win two Nobel prizes in scientific categories — won her second Nobel Prize in 1911 “in recognition of her services to the advancement of chemistry by the discovery of the elements radium and polonium, by the isolation of radium and the study of the nature and compounds of this remarkable element.”

  3. arXiv — 2035720

    arXiv “hosts more than 2,035,720 scholarly articles in the fields of physics, mathematics, computer science, quantitative biology, quantitative finance, statistics, electrical engineering and systems science, and economics.” arXiv was founded by Paul Ginsparg in 1991 and is now maintained and operated by Cornell Tech.

  4. Alexa — 11614

    Alexa was introduced to the world on Nov. 6, 2014. Now, eight years later, customers in more than 80 countries interact with Alexa billions of times each week, and Amazon and Lockheed Martin are sending the first Alexa to space as part of Callisto, a technology demonstration on NASA's upcoming Artemis I mission.

  5. Albert Einstein — 1879

    Albert Einstein was born in Ulm, in Württemberg, Germany, on March 14, 1879. He was awarded the Nobel Prize in Physics in 1921 “for his services to Theoretical Physics, and especially for his discovery of the law of the photoelectric effect.”

  6. USC Viterbi School of Engineering — 7,930,681,085

    USC’s engineering school is named for Andrew Viterbi who earned one of the first doctorates in electrical engineering ever granted at USC. The Viterbi Algorithm, a mathematical formula to eliminate signal interference, paved the way for the widespread use of cellular technology.

  7. Amazon — Lab126

    Located in Sunnyvale, Calif., the team at Lab126 designs and engineers the Amazon Astro robot, Fire tablets, Kindle e-readers, Amazon Fire TV, Amazon Echo, and other devices. They’re also exploring how devices are accidentally damaged — and how to help ensure they survive more of those incidents.

  8. Katherine Johnson — 71962

    Katherine Johnson did the trajectory analysis for NASA’s Friendship 7 before it launched in 1962. The complexity of the flight required the construction of a worldwide communications network, but astronauts were wary of the electronic calculating machines. John Glenn asked to have Johnson run the numbers by hand. “If she says they’re good,’” Johnson recalled Glenn saying, “then I’m ready to go.” Glenn’s flight was a success.

  9. Columbia Engineering — 1150

    Edwin Armstrong developed FM radio on Columbia's campus at 1150 Amsterdam Avenue in New York. During an IRE conference in 1935, he described FM radio “and then turned on his receiver in front of the audience. An FM transmission … came in totally free of static and, thanks to the wide audio spectrum being used, with a fidelity never heard before. A stunned audience listened to a live music performance transmitted with remarkable clarity and to a series of sounds, such as a glass of water being poured or a piece of paper being torn — which would have been unrecognizable over AM radio.”

  10. Amazon S3 — 16

    Amazon S3 (Simple Storage Service) is an object storage service that offers industry-leading scalability, data availability, security, and performance. It was launched 16 years ago on Pi Day, as the first generally available AWS service. At the 2021 ACM Symposium on Operating Systems Principles, Amazon researchers won a best-paper award for their work using automated reasoning to validate that ShardStore — a new S3 storage node microservice — will do what it’s supposed to.

  11. Alan Turing — 186

    Alan Turing, WWII enigma codebreaker and father of computer science, had an IQ of 186. In 1935, when Turing was 22 years old, he wrote a paper titled, “On Computable Numbers, With an Application to the Entscheidungsproblem” (German for “decision problem”). The paper is widely recognized as having provided “a conceptual model for modern computers.”

  12. UCLA Samueli School of Engineering — 3420

    The first internet transmission was sent on Oct. 29, 1969 from 3420 Boelter Hall at UCLA. The message sent to Stanford Research Institute on the evening of Oct. 29 was meant to be “LOGIN.” However, the system crashed, so the first message sent over the internet was: “LO.” The next attempt was a success, and the original Interface Message Processor, known as IMP No. 1, the equivalent to today’s router, still stands in Boelter Hall.

  13. Amazon Research Awards — 385132

    Amazon, via the Amazon Research Awards (ARA) program, has funded more than 385 research proposals at 132 universities since 2018. The ARA program funds academic research and related contributions to open-source projects by top academic researchers who have used their research awards to help improve MRI scans, create computational simulations of the human heart, understand the impact of aerosol-cloud interactions on climate, and teach robots to behave like schools of fish.

  14. Grace Hopper — 6

    The Cray XE6 “Hopper” supercomputer was named after computer science pioneer Grace Hopper. One of the first three computer “programmers,” Hopper was responsible for programming the Mark I. As head programmer for Remington Rand, she worked on the UNIVAC I (Universal Automatic Computer). In 1952 her programming team developed the first computer language “compiler” called A-0. Her team also developed Flow-Matic, the first programming language to use English-like commands.

  15. Caltech — 9019

    Scientists and engineers at Caltech and NASA’s Jet Propulsion Laboratory (JPL) landed the Mars Pathfinder on Mars on July 4, 1997 and have been operating rovers ever since — or for 9019 Earth days on March 14. Over a three-month period, Pathfinder returned 2.3 billion bits of information, including more than 16,500 images from the lander and 550 images from the rover, as well as more than 15 chemical analyses of rocks and soil and extensive data on winds and other weather factors.

  16. Blue Origin — 19314

    New Shepard has flown 19 consecutive successful launches, including 3 flights with a total of 14 astronauts aboard. Named after Mercury astronaut Alan Shepard, the first American to go to space, New Shepard is “a reusable suborbital rocket system designed to take astronauts and research payloads past the Kármán line – the internationally recognized boundary of space.”

  17. Georgia Tech — 161972

    John Young, who became the 9th person to walk on the moon in 1972, graduated from Georgia Tech's Guggenheim School of Aerospace Engineering. Young served as commander of Apollo 16, spending three nights on the moon’s surface and driving 16 miles in a lunar rover. Young was also at the helm for the first space shuttle mission, STS-1, in April 1981.

  18. University of Washington — 14492

    Waldo Semon, a University of Washington alumnus, conducted 14,492 experiments to develop synthetic rubber used during WWII. Semon is best known for inventing vinyl, the world's second most-used plastic. Semon held 116 patents, and was inducted into the Invention Hall of Fame in 1995 at age 97.

  19. Alexa Prize — 24806391

    There have been more than 24,806,391 interactions with Alexa Prize socialbots. That number will only continue to climb as the competition meant to help advance the science of conversational AI continues. Last year, Team Alquist from Czech Technical University won the Alexa Prize SocialBot Grand Challenge 4 competition.

Related content

US, WA, Seattle
The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through novel generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace ecosystem. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising. Key job responsibilities As an applied scientist on our team, you will * Develop AI solutions for Sponsored Brands advertiser and shopper experiences. Build recommendation systems that leverage generative models to develop and improve campaigns. * You invent and design new solutions for scientifically-complex problem areas and/or opportunities in new business initiatives. * You drive or heavily influence the design of scientifically-complex software solutions or systems, for which you personally write significant parts of the critical scientific novelty. You take ownership of these components, providing a system-wide view and design guidance. These systems or solutions can be brand new or evolve from existing ones. * Define a long-term science vision and roadmap for our Sponsored Brands advertising business, driven from our customers' needs, translating that direction into specific plans for applied scientists and engineering teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding. * Work closely with engineers and product managers to design, implement and launch AI solutions end-to-end; * Design and conduct A/B experiments to evaluate proposed solutions based on in-depth data analyses; * Think big about the arc of development of Gen AI over a multi-year horizon, and identify new opportunities to apply these technologies to solve real-world problems * Effectively communicate technical and non-technical ideas with teammates and stakeholders; * Translate complex scientific challenges into clear and impactful solutions for business stakeholders. * Mentor and guide junior scientists, fostering a collaborative and high-performing team culture. * Stay up-to-date with advancements and the latest modeling techniques in the field About the team The Sponsored Brands Impressions-based Offerings team is responsible for evolving the value proposition of Sponsored Brands to drive brand advertising in retail media at scale, helping brands get discovered, acquire new customers and sustainably grow customer lifetime value. We build end-to-end solutions that enable brands to drive discovery, visibility and share of voice. This includes building advertiser controls, shopper experiences, monetization strategies and optimization features. We succeed when (1) shoppers discover, engage and build affinity with brands and (2) brands can grow their business at scale with our advertising products. #GenAI
US, CA, San Diego
The Private Brands team is looking for a Sr. Research Scientist to join the team in building science solutions at scale. Our team applies Optimization, Machine Learning, Statistics, Causal Inference, and Econometrics/Economics to derive actionable insights about the complex economy of Amazon’s retail business and develop Statistical Models and Algorithms to drive strategic business decisions and improve operations. We are an interdisciplinary team of Scientists, Engineers, PMTs and Economists. Key job responsibilities You will work with business leaders, scientists, and economists to translate business and functional requirements into concrete deliverables, including the design, development, testing, and deployment of highly scalable optimization solutions and ML models. This is a unique, high visibility opportunity for someone who wants to have business impact, dive deep into large-scale problems, enable measurable actions on the consumer economy, and work closely with scientists and economists. As a Sr Scientist, 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. 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. We are particularly interested in candidates with experience in Operations Research, ML and predictive models and working with distributed systems. Academic and/or practical background in Operations Research and Machine Learning specifically Reinforcement Learning are particularly relevant for this position. To know more about Amazon science, Please visit https://www.amazon.science About the team We are a one pizza, agile team of scientists focused on solving supply chain challenges for Amazon Private Brands products. We collaborate with Amazon central teams like SCOT and develop both central as well as APB-specific solutions to address various challenges, including sourcing, demand forecasting, ordering optimization, inventory distribution, and inventory health management. Working closely with business stakeholders, Product Management Teams (PMTs), and engineering partners, we drive projects from initial concept through production deployment and ongoing monitoring.
US, CA, Sunnyvale
As a Reinforcement Learning Controls Scientist, you will be responsible for developing Reinforcement Learning models to control complex electromechanical systems. You will take responsibility for defining frameworks, performing analysis, and training models that guide and inform mechanical and electrical designs, software implementation, and other software modules that affect overall device safety and performance. You understand trade-offs between model-based and model-free approaches. You will demonstrate cross-functional collaboration and influence to accomplish your goals. You will play a role in defining processes and methods to improve the productivity of the entire team. You will interface with Amazon teams outside your immediate organization to collaborate and share knowledge. You will investigate applicable academic and industry research, prototype and test solutions to support product features, and design and validate production designs that deliver an exceptional user experience. Key job responsibilities - Produce models and simulations of complex, high degree-of-freedom dynamic electromechanical systems - Train Reinforcement Learning control policies that achieve performance targets within hardware and software constraints - Hands-on prototyping and testing of physical systems in the lab - Influence hardware and software design decisions owned by other teams to optimize system-level performance - Work with cross-functional teams (controls, firmware, perception, planning, sensors, mechanical, electrical, etc.) to solve complex system integration issues - Define key performance indicators and allocate error budgets across hardware and software modules - Perform root cause analysis of system-level failures and distinguish between hardware/software failures and hardware/software mitigations - Translate business requirements to engineering requirements and identify trade-offs and sensitivities - Mentor junior engineers in good design practice; actively participate in hiring of new team members About the team The Dynamic Systems and Control team develops models, algorithms, and code to bridge hardware and software development teams and bring robotic products to life. We contributed to Amazon Astro (https://www.amazon.com/Introducing-Amazon-Astro/dp/B078NSDFSB) and Echo Show 10 (https://www.amazon.com/echo-show-10/dp/B07VHZ41L8/), along with several new technology introductions and unannounced products currently in development.
US, WA, Seattle
About Sponsored Products and Brands: The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through industry leading generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising. About Our Team: The Sponsored Brands Impressions-based Offerings team is responsible for evolving the value proposition of Sponsored Brands to drive brand advertising in retail media at scale, helping brands get discovered, acquire new customers and sustainably grow customer lifetime value. We build end-to-end solutions that enable brands to drive discovery, visibility and share of voice. This includes building advertiser controls, shopper experiences, monetization strategies and optimization features. We succeed when (1) shoppers discover, engage and build affinity with brands and (2) brands can grow their business at scale with our advertising products. About This Role: As a Principal Scientist for the team, you will have the opportunity to apply your deep subject matter expertise in the area of ML, LLM and GenAI models. You will invent new product experiences that enable novel advertiser and shopper experiences. This role will liaise with internal Amazon partners and work on bringing state-of-the-art GenAI models to production, and stay abreast of the latest developments in the space of GenAI and identify opportunities to improve the efficiency and productivity of the team. Additionally, you will define a long-term science vision for our advertising business, driven by our customer’s needs, and translate it into actionable plans for our team of applied scientists and engineers. This role will play a critical role in elevating the team’s scientific and technical rigor, identifying and implementing best-in-class algorithms, methodologies, and infrastructure that enable rapid experimentation and scaling. You will communicate learnings to leadership and mentor and grow Applied AI talent across org. * Develop AI solutions for Sponsored Brands advertiser and shopper experiences. Build monetization and optimization systems that leverage generative models to value and improve campaign performance. * Define a long-term science vision and roadmap for our Sponsored Brands advertising business, driven from our customers' needs, translating that direction into specific plans for applied scientists and engineering teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding. * Design and conduct A/B experiments to evaluate proposed solutions based on in-depth data analyses. * Effectively communicate technical and non-technical ideas with teammates and stakeholders. * Stay up-to-date with advancements and the latest modeling techniques in the field. * Think big about the arc of development of Gen AI over a multi-year horizon and identify new opportunities to apply these technologies to solve real-world problems. #GenAI
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 a Data Scientist on our team, you'll analyze complex data, develop statistical methodologies, and provide critical insights that shape how we optimize our solutions. Working closely with our Applied Science team, you'll help build robust analytical frameworks to improve healthcare outcomes. This role offers a unique opportunity to impact healthcare through data-driven innovation. Key job responsibilities In this role, you will: - Analyze complex healthcare data to identify patterns, trends, and insights - Develop and validate statistical methodologies - Create and maintain analytical frameworks - Provide recommendations on data collection strategies - Collaborate with Applied Scientists to support model development efforts - Design and implement statistical analyses to validate analytical approaches - Present findings to stakeholders and contribute to scientific publications - Work with cross-functional teams to ensure solutions are built on sound statistical foundations - Design and implement causal inference analyses to understand underlying mechanisms - Develop frameworks for identifying and validating causal relationships in complex systems - Work with stakeholders to translate causal insights into actionable recommendations A day in the life You'll work with large-scale healthcare datasets, conducting sophisticated statistical analyses to generate actionable insights. You'll collaborate with Applied Scientists to validate model predictions and ensure statistical rigor in our approach. Regular interaction with product teams will help translate analytical findings into practical improvements for our services. About the team We represent Amazon's ambitious vision to solve the world's most pressing challenges. We are exploring new approaches to enhance research practices in the healthcare space, leveraging Amazon's scale and technological expertise. We operate with the agility of a startup while backed by Amazon's resources and operational excellence. We're looking for builders who are excited about working on ambitious, undefined problems and are comfortable with ambiguity.
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 healthcare. 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. This role offers a unique opportunity to work on projects that could fundamentally transform healthcare outcomes. Key job responsibilities In this role, you will: • Design and implement novel AI/ML solutions for complex healthcare challenges • Drive advancements in machine learning and data science • Balance theoretical knowledge with practical implementation • Work closely with customers and partners to understand their requirements • Navigate ambiguity and create clarity in early-stage product development • Collaborate with cross-functional teams while fostering innovation in a collaborative work environment to deliver impactful solutions • Establish best practices for ML experimentation, evaluation, development and deployment • Partner with leadership to define roadmap and strategic initiatives You’ll need a strong background in AI/ML, proven leadership skills, and the ability to translate complex concepts into actionable plans. You’ll also need to effectively translate research findings into practical solutions. A day in the life You will solve real-world problems by getting and analyzing large amounts of data, generate insights and opportunities, design simulations and experiments, and develop statistical and ML models. The team is driven by business needs, which requires collaboration with other Scientists, Engineers, and Product Managers across the Special Projects organization. You will prepare written and verbal presentations to share insights to audiences of varying levels of technical sophistication. About the team We represent Amazon's ambitious vision to solve the world's most pressing challenges. We are exploring new approaches to enhance research practices in the healthcare space, leveraging Amazon's scale and technological expertise. We operate with the agility of a startup while backed by Amazon's resources and operational excellence. We're looking for builders who are excited about working on ambitious, undefined problems and are comfortable with ambiguity.
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 healthcare. 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. This role offers a unique opportunity to work on projects that could fundamentally transform healthcare outcomes. Key job responsibilities In this role, you will: • Design and implement novel AI/ML solutions for complex healthcare challenges • Drive advancements in machine learning and data science • Balance theoretical knowledge with practical implementation • Work closely with customers and partners to understand their requirements • Navigate ambiguity and create clarity in early-stage product development • Collaborate with cross-functional teams while fostering innovation in a collaborative work environment to deliver impactful solutions • Establish best practices for ML experimentation, evaluation, development and deployment • Partner with leadership to define roadmap and strategic initiatives You’ll need a strong background in AI/ML, proven leadership skills, and the ability to translate complex concepts into actionable plans. You’ll also need to effectively translate research findings into practical solutions. A day in the life You will solve real-world problems by getting and analyzing large amounts of data, generate insights and opportunities, design simulations and experiments, and develop statistical and ML models. The team is driven by business needs, which requires collaboration with other Scientists, Engineers, and Product Managers across the Special Projects organization. You will prepare written and verbal presentations to share insights to audiences of varying levels of technical sophistication. About the team We represent Amazon's ambitious vision to solve the world's most pressing challenges. We are exploring new approaches to enhance research practices in the healthcare space, leveraging Amazon's scale and technological expertise. We operate with the agility of a startup while backed by Amazon's resources and operational excellence. We're looking for builders who are excited about working on ambitious, undefined problems and are comfortable with ambiguity.
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 healthcare. 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. This role offers a unique opportunity to work on projects that could fundamentally transform healthcare outcomes. Key job responsibilities In this role, you will: • Design and implement novel AI/ML solutions for complex healthcare challenges • Drive advancements in machine learning and data science • Balance theoretical knowledge with practical implementation • Work closely with customers and partners to understand their requirements • Navigate ambiguity and create clarity in early-stage product development • Collaborate with cross-functional teams while fostering innovation in a collaborative work environment to deliver impactful solutions • Establish best practices for ML experimentation, evaluation, development and deployment • Partner with leadership to define roadmap and strategic initiatives You’ll need a strong background in AI/ML, proven leadership skills, and the ability to translate complex concepts into actionable plans. You’ll also need to effectively translate research findings into practical solutions. A day in the life You will solve real-world problems by getting and analyzing large amounts of data, generate insights and opportunities, design simulations and experiments, and develop statistical and ML models. The team is driven by business needs, which requires collaboration with other Scientists, Engineers, and Product Managers across the Special Projects organization. You will prepare written and verbal presentations to share insights to audiences of varying levels of technical sophistication. About the team We represent Amazon's ambitious vision to solve the world's most pressing challenges. We are exploring new approaches to enhance research practices in the healthcare space, leveraging Amazon's scale and technological expertise. We operate with the agility of a startup while backed by Amazon's resources and operational excellence. We're looking for builders who are excited about working on ambitious, undefined problems and are comfortable with ambiguity.
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 a Senior Applied Scientist on our team, you will focus on building state-of-the-art ML models for healthcare. 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. This role offers a unique opportunity to work on projects that could fundamentally transform healthcare outcomes. Key job responsibilities In this role, you will: • Design and implement novel AI/ML solutions for complex healthcare challenges • Drive advancements in machine learning and data science • Balance theoretical knowledge with practical implementation • Work closely with customers and partners to understand their requirements • Navigate ambiguity and create clarity in early-stage product development • Collaborate with cross-functional teams while fostering innovation in a collaborative work environment to deliver impactful solutions • Establish best practices for ML experimentation, evaluation, development and deployment • Partner with leadership to define roadmap and strategic initiatives You’ll need a strong background in AI/ML, proven leadership skills, and the ability to translate complex concepts into actionable plans. You’ll also need to effectively translate research findings into practical solutions. A day in the life You will solve real-world problems by getting and analyzing large amounts of data, generate insights and opportunities, design simulations and experiments, and develop statistical and ML models. The team is driven by business needs, which requires collaboration with other Scientists, Engineers, and Product Managers across the Special Projects organization. You will prepare written and verbal presentations to share insights to audiences of varying levels of technical sophistication. About the team We represent Amazon's ambitious vision to solve the world's most pressing challenges. We are exploring new approaches to enhance research practices in the healthcare space, leveraging Amazon's scale and technological expertise. We operate with the agility of a startup while backed by Amazon's resources and operational excellence. We're looking for builders who are excited about working on ambitious, undefined problems and are comfortable with ambiguity.
US, MA, Boston
The Artificial General Intelligence (AGI) team is looking for a highly skilled and experienced Sr. Applied Scientist, to support the development and implementation of state-of-the-art algorithms and models for supervised fine-tuning and reinforcement learning through human feedback and complex reasoning; with a focus across text, image, and video modalities. As an Sr. Applied Scientist, you will play a critical role in supporting the development of Generative AI (Gen AI) technologies that can handle Amazon-scale use cases and have a significant impact on our customers' experiences. Key job responsibilities Collaborate with cross-functional teams of engineers, product managers, and scientists to identify and solve complex problems in Gen AI Design and execute experiments to evaluate the performance of different algorithms (PT, SFT, RL) and models, and iterate quickly to improve results Think big about the arc of development of Gen AI over a multi-year horizon, and identify new opportunities to apply these technologies to solve real-world problems Communicate results and insights to both technical and non-technical audiences, including through presentations and written reports About the team We are passionate scientists dedicated to pushing the boundaries of innovation in Gen AI with focus on Software Development use cases.