Zoox 3D map.gif
This visualization shows a Zoox vehicle aligning lidar data to Zoox's 3D map to localize itself in downtown San Francisco. Central to the Zoox navigation system is a cluster of capabilities: calibration, localization, and mapping.
Zoox

How Zoox vehicles “find themselves” in an ever-changing world

Advanced machine learning systems help autonomous vehicles react to unexpected changes.

For a human to drive successfully around an urban environment, they must be able to trust their eyes and other senses, know where they are, understand the permissible ways to move their vehicle safely, and of course know how to reach their destination.

Building these abilities, and so many more, into an autonomous electric vehicle designed to transport customers smoothly and safely around densely populated cities takes an astonishing amount of technological innovation. Since its founding in 2014, Zoox has been developing autonomous ride-hailing vehicles, and the systems that support them, from the ground up. The company, which is based in Foster City, California, became an independent subsidiary of Amazon in 2020.

Zoox Fully Autonomous Vehicle at Coit Tower San Francsico
The Zoox L5 fully autonomous, all-electric robotaxi has no forward or backward, can reach speeds of up to 75 miles per hour, and can move all four wheels independently.
Zoox

The Zoox purpose-built robot is an autonomous, pod-like electric vehicle that can carry four passengers in comfort. It has no forward or backward, being equally happy to drive in either direction, at up to 75 miles per hour, and can move all four wheels independently. There are no manual driving controls inside the vehicle.

Zoox has already done a great deal of testing of its autonomous driving systems using a fleet of retrofitted Toyota Highlander vehicles — with a human driver at the wheel, ready to take over if needed — in San Francisco, Las Vegas, Foster City, and Seattle.

Central to the Zoox navigation system is a cluster of capabilities called calibration, localization, and mapping. Only through this combination of abilities can Zoox vehicles understand their environment with exquisite precision, know where they are in relation to everything in their vicinity and beyond, and know exactly where they are going.

Zoox test vehicles, in this instance Toyota Highlanders, are retrofitted with an almost identical sensor configuration and compute system to their purpose-built vehicle.
Zoox has already done a great deal of testing of its autonomous driving systems using a fleet of Toyota Highlanders retrofitted with an almost identical sensor configuration and compute system to the purpose-built vehicle — with a human driver at the wheel, ready to take over if needed — in San Francisco, Las Vegas, Foster City, and Seattle.
Zoox

This is the domain of Zoox’s CLAMS (Calibration, Localization, and Mapping Simultaneously) and Zoox Road Network (ZRN) teams, which together enable the vehicle to meaningfully understand its location and process its surroundings. To get an idea of how these elements work in concert, Amazon Science spoke to several members of these teams.

In terms of awareness of its environment, the Zoox vehicle can fairly be likened to an all-seeing eye. Its state-of-the-art sensor architecture is made up of LiDARs (Light Detection and Ranging), radars, visual cameras, and longwave-infrared cameras. These are arrayed symmetrically around the outside of the vehicle, providing an overlapping, 360-degree field of view.

With this many sensors in play, it is critical that their input is stitched together accurately to create a true and self-consistent picture of everything happening all around the vehicle, moment to moment. To do that, the vehicle needs to know exactly where its sensors are in relation to each other, and with sensors of such high resolution, it’s not enough simply to know where the sensors were attached to the vehicle in the first place.

“To a very minor but still important degree, every vehicle is a special snowflake in some way,” says Taylor Arnicar, staff technical program manager, who oversees the CLAMS and ZRN teams. “And the other reality is we’re exposing these vehicles to rather harsh real-world conditions. There’s shock and vibe, thermal events, and all these things can cause very slight changes in sensor positioning.” Were such changes to be ignored, it could result in unacceptably “blurry” vision, Arnicar says.

In other autonomous-robotics applications, sensor calibration typically entails the robot looking at a specific calibration target, displayed on surrounding infrastructure, such as a wall. With the Zoox vehicle destined for the ever-changing urban environment, the Zoox team is pioneering infrastructure-free calibration.

This animation shows a Zoox system aligning color camera edges to lidar depth edges
This animation shows a Zoox system aligning color camera edges to lidar depth edges. With the Zoox vehicle destined for the ever-changing urban environment, the Zoox team is pioneering infrastructure-free calibration.
Zoox

“That means we rely on the natural environment — whatever objects, shapes, and colors are in the world around the vehicle as it drives,” says Arnicar. One way the team does this is by automatically identifying image gradients — such as the edges of buildings or the trunks of trees — from the vehicle’s color camera data and aligning those with depth edges in the LiDAR data.

It is worth emphasizing that a superpower of the Zoox vehicle is seeing its surroundings with superhuman perception. With so many sensors mounted externally, in pods on the corners of the vehicles, it can see what’s coming around every corner before a human driver would. Its LiDARs and visual cameras mean it knows what lies in every direction with high precision. It even boasts a kind of X-ray vision: “Certain materials don’t obstruct the radar,” says Elena Strumm, Zoox’s engineering manager for mapping algorithms. “When a bicyclist is cycling behind a bush, for example, we might get a really clear radar signature on them, even if that bush has occluded the LiDAR and visual cameras.”

Related content
Jesse Levinson, co-founder and CTO of Zoox, answers 3 questions about the challenges of developing autonomous vehicles and why he’s excited about Zoox’s robotaxi fleet.

Now that the vehicle can rely on what it senses, it needs a map. The Zoox team gathers its map data first-hand by driving around the cities in which it will operate in Toyota Highlanders retrofitted with the full Zoox sensor architecture. LiDAR data and visual images collected in this way can be made into high-definition maps by the CLAMS team. But first, all the people, cars, and other ephemeral aspects of the urban landscape must be removed from the LiDAR data. For this, machine learning is required.

When the Zoox vehicle is in normal urban operations, it is fundamental that its perception system recognizes the aspects of incoming LiDAR data that represent pedestrians, cyclists, cars or trucks — or indeed anything that may move in ways that need to be anticipated. LiDARs create enormous amounts of information about the dynamic 3D environment around the vehicle in the form of “point clouds” — sets of points that describe the objects and surfaces visible to the LiDAR. Using machine learning to instantly identify people in a fast-moving, dynamic environment is a challenge, particularly as people may be moving, static, partly occluded, in a wheelchair, only visible from the knees down, or any number of possibilities.

A raw lidar point cloud of Caesars Palace in Las Vegas, before it’s turned into an efficient mesh representation for the 3D map.
A raw lidar point cloud of Caesars Palace in Las Vegas, before it’s turned into an efficient mesh representation for the 3D map.
Zoox

“Machine-learned AI systems excel at this kind of pattern-matching problem. You feed millions of examples of something and then they can do a great good job of recognizing that thing in the abstract,” Arnicar explains.

In a beautiful piece of synergy, the Zoox mapping team benefits from this safety-critical application of machine learning because they require the reverse information — they want to take the people and cars out of the data so that they can create 3D maps of the road landscape and infrastructure alone.

“Once these elements are identified and removed from the mapping data, it becomes possible to combine LiDAR-based point clouds from overlapping locations to create high resolution 3D maps,” says Strumm.

But maps are not useful to the vehicle without meaning. To create a “semantic map,” the ZRN team adds layers of information to the 3D map that encode everything static that the vehicle needs to navigate the road safely, including speed limits, traffic light locations, one-way streets, keep-clear zones and more.

Related content
Deep learning to produce invariant representations, estimations of sensor reliability, and efficient map representations all contribute to Astro’s superior spatial intelligence.

The final core piece of the CLAMS team’s work is localization. Zoox’s localization technology allows each vehicle to know where it is in the world — and on its map — to within a few centimeters, and its direction to within a fraction of a degree. The vehicle does this not only by comparing its visual inputs with its map, but also by utilizing GPS, accelerometers, wheel speeds, gyroscopes, and more. It can therefore check its precise location and velocity hundreds of times per second. Armed with a combination of the physical and semantic maps, and always aware of its place in relation to every object or person in its vicinity, the vehicle can navigate safely to its destination.

Part of the localization challenge is that any map will become dated over time, Arnicar explains. “Once you build the map — from the moment the data is collected — you need to consider that it could be out of date.” This is because the world can change anytime, anywhere, without notice. “On one occasion one of our Toyota Highlanders was driving down the street collecting data, and right in front of us was a construction truck with a guy hanging off the back, repainting the lane line in a different place as they drove along. No amount of fast mapping can catch up with these sorts of scenarios.” In practice, this means the map needs to be treated as a guidebook for the vehicle, not as gospel.

“This changeability of the real world led us to create the ZRN Monitor, a system on the vehicle that determines whether the actual road environment has differed from our semantic map data,” says Chris Gibson, engineering manager for the Zoox Road Network team. “For example, if lane markings have changed and now the double yellow lines have moved, then if we don’t detect that dynamically, we could potentially end up driving into opposing traffic. From a safety perspective, we must make absolutely certain that the vehicle does not drive into such areas.” The ZRN Monitor’s role is to identify and, to an extent, evaluate the safety implications of such unanticipated environmental modifications. These notifications are also an indication that it may be time to update the map for that area with more recent sensor data.

In the uncommon situation in which the vehicle encounters a challenging driving situation and it isn’t highly confident of a safe way to proceed, it can request “TeleGuidance” — a human operator located in a dedicated service center is provided with the full 3D understanding of the vehicle’s environment, as well as live-streamed sensor data.

A Zoox TeleGuidance tactician providing remote guidance to a vehicle from the Zoox HQ
A Zoox TeleGuidance tactician provides remote guidance to a vehicle from Zoox HQ.
Zoox

“Imagine a construction zone. The Zoox vehicle might need to be directed to drive on the other side of the road, which would normally carry oncoming traffic. That’s a rule that under most circumstances you shouldn’t break, but in this instance, a TeleGuidance tactician might provide the robot with waypoints to ensure it knows where it needs to go in that moment,” says Gibson. The vehicle remains responsible for the safety of its passengers, however, and continues to drive autonomously at all times while acting on the TeleGuidance information.

Before paying customers will be able to use their smartphones to hail a Zoox vehicle, more on-road testing first needs to be done. Zoox has built dozens of its purpose-built vehicles and is testing them on “semi-private courses” in California, according to Zoox’s co-founder and chief technology officer, Jesse Levinson. Next on the agenda is full testing on public roads, says Levinson, who promises that is “really not that far away. We’re not talking about years.”

So, what does it feel like to be transported in a Zoox vehicle?

“I’ve ridden in a Zoox vehicle, with no safety driver, no steering wheel, no anything — just me in the vehicle,” says Arnicar. “And it is magical. It’s what I’ve been working at Zoox seven years to experience. I’ve seen Zoox go from sketches on a napkin to something I can ride in. That's pretty amazing.”

When an autonomous Zoox vehicle ultimately comes around a corner near you, know this for a fact: no matter how striking and novel it looks, it will see you before you see it.

Research areas

Related content

US, MA, North Reading
Are you inspired by invention? Is problem solving through teamwork in your DNA? Do you like the idea of seeing how your work impacts the bigger picture? Answer yes to any of these and you’ll fit right in here at Amazon Robotics. We are a smart team of doers that work passionately to apply cutting edge advances in robotics and software to solve real-world challenges that will transform our customers’ experiences in ways we can’t even imagine yet. We invent new improvements every day. We are Amazon Robotics and we will give you the tools and support you need to invent with us in ways that are rewarding, fulfilling and fun. Amazon Robotics is seeking Applied Science Interns and Co-ops with a passion for robotic research to work on cutting edge algorithms for robotics. Our team works on challenging and high-impact projects within robotics. Examples of projects include allocating resources to complete a million orders a day, coordinating the motion of thousands of robots, autonomous navigation in warehouses, identifying objects and damage, and learning how to grasp all the products Amazon sells. As an Applied Science Intern/Co-op at Amazon Robotics, you will be working on one or more of our robotic technologies such as autonomous mobile robots, robot manipulators, and computer vision identification technologies. The intern/co-op project(s) and the internship/co-op location are determined by the team the student will be working on. Please note that by applying to this role you would be considered for Applied Scientist summer intern, spring co-op, and fall co-op roles on various Amazon Robotics teams. These teams work on robotics research within areas such as computer vision, machine learning, robotic manipulation, navigation, path planning, perception, optimization and more. Learn more about Amazon Robotics: https://amazon.jobs/en/teams/amazon-robotics
CA, ON, Toronto
Amazon Advertising is one of Amazon's fastest growing and most profitable businesses, responsible for defining and delivering a collection of advertising products that drive discovery and sales. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day! As an Applied Scientist on this team, you will: - Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale, complexity. - Perform hands-on analysis and modeling of enormous data sets to develop insights that increase traffic monetization and merchandise sales, without compromising the shopper experience. - Build machine learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production; work closely with software engineers to assist in productionizing your ML models. - Run A/B experiments, gather data, and perform statistical analysis. - Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving. - Research new and innovative machine learning approaches. - Recruit Applied Scientists to the team and provide mentorship. Why you will love this opportunity: Amazon is investing heavily in building a world-class advertising business. This team defines and delivers a collection of advertising products that drive discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazon’s Retail and Marketplace businesses. We deliver billions of ad impressions, millions of clicks daily, and break fresh ground to create world-class products. We are a highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit - with a broad mandate to experiment and innovate. Impact and Career Growth: You will invent new experiences and influence customer-facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest-growing businesses across all of Amazon! Define a long-term science vision for our advertising business, driven from our customers' needs, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding. Team video https://youtu.be/zD_6Lzw8raE
US, WA, Seattle
Amazon Advertising is one of Amazon's fastest growing and most profitable businesses, responsible for defining and delivering a collection of advertising products that drive discovery and sales. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day! As the Data Science Manager on this team, you will: - Lead of team of scientists, business intelligence engineers, etc., on solving science problems with a high degree of complexity and ambiguity. - Develop science roadmaps, run annual planning, and foster cross-team collaboration to execute complex projects. - Perform hands-on data analysis, build machine-learning models, run regular A/B tests, and communicate the impact to senior management. - Hire and develop top talent, provide technical and career development guidance to scientists and engineers in the organization. - Analyze historical data to identify trends and support optimal decision making. - Apply statistical and machine learning knowledge to specific business problems and data. - Formalize assumptions about how our systems should work, create statistical definitions of outliers, and develop methods to systematically identify outliers. Work out why such examples are outliers and define if any actions needed. - Given anecdotes about anomalies or generate automatic scripts to define anomalies, deep dive to explain why they happen, and identify fixes. - Build decision-making models and propose effective solutions for the business problems you define. - Conduct written and verbal presentations to share insights to audiences of varying levels of technical sophistication. Why you will love this opportunity: Amazon has invested heavily in building a world-class advertising business. This team defines and delivers a collection of advertising products that drive discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazon’s Retail and Marketplace businesses. We deliver billions of ad impressions, millions of clicks daily, and break fresh ground to create world-class products. We are a highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit - with a broad mandate to experiment and innovate. Impact and Career Growth: You will invent new experiences and influence customer-facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest-growing businesses across all of Amazon! Define a long-term science vision for our advertising business, driven from our customers' needs, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding. Team video ~ https://youtu.be/zD_6Lzw8raE
US, WA, Seattle
Amazon Advertising is one of Amazon's fastest growing and most profitable businesses, responsible for defining and delivering a collection of advertising products that drive discovery and sales. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day! As an Applied Science Manager in Machine Learning, you will: - Directly manage and lead a cross-functional team of Applied Scientists, Data Scientists, Economists, and Business Intelligence Engineers. - Develop and manage a research agenda that balances short term deliverables with measurable business impact as well as long term investments. - Lead marketplace design and development based on economic theory and data analysis. - Provide technical and scientific guidance to team members. - Rapidly design, prototype and test many possible hypotheses in a high-ambiguity environment, making use of both quantitative and business judgment - Advance the team's engineering craftsmanship and drive continued scientific innovation as a thought leader and practitioner. - Develop science and engineering roadmaps, run annual planning, and foster cross-team collaboration to execute complex projects. - Perform hands-on data analysis, build machine-learning models, run regular A/B tests, and communicate the impact to senior management. - Collaborate with business and software teams across Amazon Ads. - Stay up to date with recent scientific publications relevant to the team. - Hire and develop top talent, provide technical and career development guidance to scientists and engineers within and across the organization. Why you will love this opportunity: Amazon is investing heavily in building a world-class advertising business. This team defines and delivers a collection of advertising products that drive discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazon’s Retail and Marketplace businesses. We deliver billions of ad impressions, millions of clicks daily, and break fresh ground to create world-class products. We are a highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit - with a broad mandate to experiment and innovate. Impact and Career Growth: You will invent new experiences and influence customer-facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest-growing businesses across all of Amazon! Define a long-term science vision for our advertising business, driven from our customers' needs, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding. Team video ~ https://youtu.be/zD_6Lzw8raE
US, NJ, Newark
At Audible, we believe stories have the power to transform lives. It’s why we work with some of the world’s leading creators to produce and share audio storytelling with our millions of global listeners. We are dreamers and inventors who come from a wide range of backgrounds and experiences to empower and inspire each other. Imagine your future with us. ABOUT THIS ROLE As Senior Data Scientist, you will build scalable solutions and models to support our business functions (Marketing, Product, Content). Leveraging a range of methods including machine learning and simulation, you will explain, quantify, predict and prescribe in support of informing critical business decisions. You will translate business goals into agile, insightful analytics. You will seek to create value for both stakeholders and customers and inform findings in a clear, actionable way to managers and senior leaders. ABOUT THE TEAM Audible data science team partners with marketing, content, product, and technology teams to solve business and technology problems using scientific approaches to build product and services that surprise and delight our customers. We employ scalable cutting-edge machine learning (ML), causal inference (CI) and GenAI / Natural Language Processing (NLP) knowledge to better target customers and prospects, understand and personalize the content, and context needed to optimize their book-listening experience. We operate in an agile environment in which we own and collaborate on the life cycle of research, design, and model development of relevant projects. ABOUT YOU We are looking for a motivated, results-oriented Data Scientist with strong rigor and demonstrable skills in ML, CI, NLP, data mining and/or large-scale distributed computation. As a Senior Data Scientist, you will... - Develop and validate models to optimize the Who, When, Where and How of all our interactions with customers - Develop Amazon-scale data engineering pipelines - Imagine and invent before the business asks, and create groundbreaking applications using cutting-edge approaches - Develop compelling data visualizations - Work closely with other data scientists, ML experts, engineers as well as business across globe, and on cross-disciplinary efforts with other scientists within Amazon - Contribute to the growth of the Audible Data Science team by sharing your ideas, intellectual property and learning from others ABOUT AUDIBLE Audible is the leading producer and provider of audio storytelling. We spark listeners’ imaginations, offering immersive, cinematic experiences full of inspiration and insight to enrich our customers daily lives. Our Hub+Home hybrid workplace model gives employees the flexibility between gathering in a common office space (work from hub) and remote work (work from home). For more information, please visit adbl.co/hybrid
US, CA, Sunnyvale
The Amazon Artificial General Intelligence (AGI) Personalization team is looking for a passionate, highly skilled and inventive Applied Scientist with strong machine learning background to build state-of-the-art ML systems for personalizing large-scale, high-quality conversational assistant systems. As a Applied Scientist, you will play a critical role in driving the development of personalization techniques enabling conversational systems, in particular those based on large language models, information retrieval, recommender systems and knowledge graph, to be tailored to customer needs. You will handle Amazon-scale use cases with significant impact on our customers' experiences. Key job responsibilities - Use deep learning, ML and NLP techniques to create scalable solutions for creation and development of language model centric solutions for building personalized assistant systems based on a rich set of structured and unstructured contextual signals - Innovate new methods for contextual knowledge extraction and information retrieval, using language models in combination with other learning techniques, that allows effective grounding in context providers when considering memory, compute, latency and quality - Research in advanced customer understanding and behavior modeling techniques - Collaborate with cross-functional teams of scientists, engineers, and product managers to identify and solve complex problems in personal knowledge aggregation, processing, modeling, and verification - Design and execute experiments to evaluate the performance of state-of-the-art algorithms and models, and iterate quickly to improve results - Think Big on conversational assistant system personalization 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 The AGI Personalization org uses various contextual signals to personalize Large Language Model output for our customers while maintaining privacy and security of customer data. We work across multiple Amazon products, including Alexa, to enhance the user experience by bringing more personal context and relevance to customer interactions.
US, NY, New York
Amazon Advertising is one of Amazon's fastest growing and most profitable businesses. As a core product offering within our advertising portfolio, Sponsored Products (SP) helps merchants, retail vendors, and brand owners succeed via native advertising, which grows incremental sales of their products sold through Amazon. The SP team's primary goals are to help shoppers discover new products they love, be the most efficient way for advertisers to meet their business objectives, and build a sustainable business that continuously innovates on behalf of customers. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day! Why you love this opportunity Amazon is investing heavily in building a world-class advertising business. This team is responsible for defining and delivering a collection of advertising products that drive discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazon’s Retail and Marketplace businesses. We deliver billions of ad impressions, millions of clicks daily, and break fresh ground to create world-class products. We are highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit - with a broad mandate to experiment and innovate. Impact and Career Growth You will invent new experiences and influence customer-facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest-growing businesses across all of Amazon! Define a long-term science vision for our advertising business, driven fundamentally from our customers' needs, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding. Key job responsibilities Key job responsibilities As an Applied Scientist III on this team you will: * Lead complex and ambiguous projects to deliver bidding recommendation products to advertisers. * Build machine learning models and utilize data analysis to deliver scalable solutions to business problems. * Perform hands-on analysis and modeling with very large data sets to develop insights that increase traffic monetization and merchandise sales without compromising shopper experience. * Work closely with software engineers on detailed requirements, technical designs and implementation of end-to-end solutions in production. * Design and run A/B experiments that affect hundreds of millions of customers, evaluate the impact of your optimizations and communicate your results to various business stakeholders. * Work with scientists and economists to model the interaction between organic sales and sponsored content and to further evolve Amazon's marketplace. * Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving. * Research new predictive learning approaches for the sponsored products business. * Write production code to bring models into production. * Mentor junior scientists and engineer in the team.
CA, ON, Toronto
Amazon Advertising is one of Amazon's fastest growing and most profitable businesses. As a core product offering within our advertising portfolio, Sponsored Products (SP) helps merchants, retail vendors, and brand owners succeed via native advertising, which grows incremental sales of their products sold through Amazon. The SP team's primary goals are to help shoppers discover new products they love, be the most efficient way for advertisers to meet their business objectives, and build a sustainable business that continuously innovates on behalf of customers. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day! Why you love this opportunity Amazon is investing heavily in building a world-class advertising business. This team is responsible for defining and delivering a collection of advertising products that drive discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazon’s Retail and Marketplace businesses. We deliver billions of ad impressions, millions of clicks daily, and break fresh ground to create world-class products. We are highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit - with a broad mandate to experiment and innovate. Impact and Career Growth You will invent new experiences and influence customer-facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest-growing businesses across all of Amazon! Define a long-term science vision for our advertising business, driven fundamentally from our customers' needs, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding. Key job responsibilities As an Applied Scientist on this team you will: * Build machine learning models and utilize data analysis to deliver scalable solutions to business problems. * Perform hands-on analysis and modeling with very large data sets to develop insights that increase traffic monetization and merchandise sales without compromising shopper experience. * Work closely with software engineers on detailed requirements, technical designs and implementation of end-to-end solutions in production. * Design and run A/B experiments that affect hundreds of millions of customers, evaluate the impact of your optimizations and communicate your results to various business stakeholders. * Work with scientists and economists to model the interaction between organic sales and sponsored content and to further evolve Amazon's marketplace. * Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving. * Research new predictive learning approaches for the sponsored products business. * Write production code to bring models into production.
US, WA, Bellevue
The Artificial General Intelligent team (AGI) seeks a passionate, talented, and resourceful Applied Scientist in the field of LLM, Artificial Intelligence (AI), Natural Language Processing (NLP) and/or Information Retrieval, to invent and build scalable solutions for a state-of-the-art context-aware conversational AI. As part of this team, you will collaborate with talented peers to create scalable solutions for an innovative conversational assistant, aiming to revolutionize user experiences for millions of Alexa customers. The ideal candidate possesses a solid understanding of machine learning fundamentals and a passion for pushing boundaries in the field. They thrive in fast-paced environments, possess the drive to tackle complex challenges, and excel at swiftly delivering impactful solutions while iterating based on user feedback. Join us in our mission to redefine industry standards and provide unparalleled experiences for our customers. Key job responsibilities . You will analyze, understand and improve user experiences by leveraging Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in artificial intelligence. . You will work on core LLM technologies, including developing best-in-class modeling, prompt optimization algorithms to enable Conversation AI use cases · Build and measure novel online & offline metrics for personal digital assistants and customer scenarios, on diverse devices and endpoints · Create, innovate and deliver deep learning, policy-based learning, and/or machine learning based algorithms to deliver customer-impacting results · Perform model/data analysis and monitor metrics through online A/B testing · Research and implement novel machine learning and deep learning algorithms and models.
US, CA, Santa Clara
AWS is looking for world class scientists and engineers to join Amazon Q Developer Machine Learning team to develop groundbreaking generative AI technologies like Amazon Q and CodeWhisperer. Our scientists push boundaries in training large language models, code generation, retrieval-augmented generation, and beyond to invent creative solutions. You will invent, implement, and deploy state-of-the-art machine learning solutions at Amazon scale, having a direct impact on revolutionary products used by millions. You will make breakthroughs that challenge the limits of AI and machine learning while collaborating with leading academics and interacting directly with customers to bring new research rapidly to production. You will publish your work at top Machine Learning and Natural Language Processing conferences. AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS. Within AWS UC, Amazon Dedicated Cloud (ADC) roles engage with AWS customers who require specialized security solutions for their cloud services. A day in the life Diverse Experiences AWS 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 AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & 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, mentorship 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 we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Hybrid Work We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our U.S. Amazon offices. About the team The Amazon Web Services (AWS) Next Gen DevX (NGDE) team uses generative AI and foundation models to reimagine the experience of all builders on AWS. From the IDE to web-based tools and services, AI will help engineers work on large and small applications. We explore new technologies and find creative solutions. Curiosity and an explorative mindset can find a place here to impact the life of engineers around the world. If you are excited about this space and want to enlighten your peers with new capabilities, this is the team for you.