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SimBot Challenge FAQs

Frequently asked questions about the challenge.
General
General
What is the Alexa Prize?
Alexa is Amazon’s cloud-based voice service available on over 100 million devices from Amazon and third-party device manufacturers. With Alexa, you can build natural voice experiences that offer customers a more intuitive way to interact with the technology they use every day. Our collection of tools, APIs, reference solutions, and documentation makes it easy for anyone to build with Alexa.
Why did Amazon create the Alexa Prize?
The Alexa Prize, an annual university competition dedicated to accelerating the field of conversational artificial intelligence (AI), was created to recognize students from around the globe who are changing the way we interact with technology. The goal is to advance several areas of conversational AI including natural language understanding (NLU), context modeling, dialog management, commonsense reasoning, natural language generation (NLG), and knowledge acquisition.
How does the Alexa Prize support research?
The Alexa Prize is a research testbed for university students to experiment with and advance conversational AI at scale.

Research teams own the intellectual property (IP) in their systems and are encouraged to publish scientific articles on their work. As described in the Official Rules, participating teams grant Amazon a non-exclusive license to any technology or software they develop in connection with the competition.
What new datasets will I have access to as part of the Alexa Prize?
The TEACh dataset as well as a training dataset proprietary to the live interaction portion of the SimBot Challenge will be available to competitors in each phase.
SimBot
What is the SimBot Challenge?
SimBot, a competition focused on helping advance development of next-generation virtual assistants that will assist humans in completing real-world tasks by continuously learning, and gaining the ability to perform commonsense reasoning.

The SimBot Challenge will have two phases: A public benchmark phase, and a live interactions phase. Participants in both phases will build machine-learning models for natural language understanding, human-robot interaction, and robotic task completion. Artificial intelligence challenges addressed in the competition relate to reasoning on language and scene understanding, learning from demonstration, self-learning, and task completion utilizing natural language.

Unlike previous Alexa Prize competitions, the public benchmark challenge phase will be open to university teams, as well as individuals in academia and industry interested in advancing the science of AI and engaging top researchers from around the globe. The SimBot Challenge public benchmark phase is like existing visual language navigation competitions.
What is the difference between the Public Benchmark Challenge and the Live Interaction Challenge?
The Public Benchmark Challenge is open to any individual or team, academic or industry, who wants to complete and submit a model for evaluation and rating during the evaluation period. It is based on the TEACh dataset offered to the research community in October, 2021. The Live Interaction Period’s participation is limited solely to the university-based teams selected for the SimBot Challenge in November 2021 and June, 2022. These teams will each receive Amazon sponsorship to build a SimBot that will compete in a challenge from July, 2022 to September 2022 where they will receive real time ratings and feedback from Alexa Users.
Why is the SimBot - Live Interaction Challenge only limited to university teams?
The SimBot Challenge - live interaction phase is part of the Alexa Prize which is currently limited to universities and university students in Amazon initiatives to advance AI. However, the Public Benchmarking Challenge is open to both academic and university-based teams.
What will my SimBot do?
SimBot will navigate in a virtual environment to complete challenges guided by Alexa users. SimBot will interact with objects in the environment including but not limited to those common to offices and homes. There will be obstacles and hazards introduced to make game play fun and challenging.
How will I build my SimBot?
SimBots will use images from the game and instructions from Alexa users to navigate in a virtual world. Teams will build AI models which recognize objects and scenes as well as understand natural language commands from users. We plan to provide baseline data and a baseline model as a reference but we expect teams to develop new and novel approaches as well as augment the provided data to improve performance.
Eligibility: Public Benchmark Challenge
Phase 1, SimBot challenge
Who is eligible to participate in the public benchmark challenge?
Any individual or team, academic or industry-based.
How do I sign up to participate in the public benchmark challenge?
A registration form will open on November 15, 2021 at alexaprize.com.
Is funding available to university teams competing in the public benchmark challenge?
No, funding is only available to university teams selected to participate in the SimBot Challenge. In addition to the teams selected in 2021 up to four new, high-performing teams from the public benchmark challenge will be invited to apply for the SimBot challenge, live interaction phase for which funding is available. Learn more here.
Who can apply to participate?
Any individual or team can register and participate in the public benchmark phase with exception of parties from Cuba, Iran, North Korea, Sudan, Syria, and the region of Crimea.

Registration for the public benchmark challenge will open November 15, 2021. The challenge will begin on January 10, 2022.
Do I need to be a certain age?
Participants must be at or above the age of majority in the country, state, province or jurisdiction of residence at the time of registration.
Can I enroll if a family member is an Amazon employee?
Immediate family members and household members of Amazon employees, directors and contractors are not eligible to participate.
Eligibility: SimBot Challenge
Includes sponsored teams for both Public Benchmark and Live Interaction phases
Who can apply to participate?
The Alexa Prize is open to full-time students enrolled in an accredited university, with the exception of universities in Cuba, Iran, North Korea, Sudan, Syria, and the region of Crimea (see Official Rules). Proof of enrollment will be required to participate.
Can I participate if I don’t attend a university?
No. The Alexa Prize is open only to full-time enrolled university students.
Do I need to be enrolled in a university program throughout the duration of the competition?
All participating team members must remain full-time students in good standing at their university while participating in the competition.
Do I need to be a certain age?
Participants must be at or above the age of majority in the country, state, province or jurisdiction of residence at the time of entry.
Can I enroll if a family member is an Amazon employee?
Immediate family members and household members of Amazon employees, directors and contractors are not eligible to participate. See Official Rules for additional restrictions.
If my team fails to apply for the SimBot Challenge now, will there be any future opportunities to compete in the Live Interaction challenge?
Yes, the initial application period run from October 4-31, 2021. In addition to the teams selected in 2021 up to four new, high-performing university teams from the public benchmark challenge will be invited to apply for the SimBot challenge, live interaction phase for which funding is available. Learn more here.
Will university teams selected post-Public Benchmark Challenge be eligible for funding and for what amount?
Teams selected for the SimBot Challenge in June, 2022 will be eligible for funding.
If my team was not selected during the first application period are we eligible to re-apply in may if we qualify?
Yes. University-based teams that participate in the public benchmark phase are eligible to re-apply for the SimBot challenge between May 9 - 23, 2022. Four new, high-performing university teams from the public benchmark challenge will be invited to apply for the SimBot challenge, live interaction phase for which funding is available. Learn more here.
My team is not completely comprised of university students but we perform well in the public benchmark challenge? Is there an opportunity for us to continue in the competition?
Yes, we plan to continue the public benchmark competition through the end of 2022.
My company does collaborative work with several universities, are we eligible to compete in the live interaction challenge alongside them?
No, only full-time students are eligible to participate in the SimBot challenge, which includes the live interaction period.
My university and another frequently collaborate on projects - is there any exception to the students all enrolled in one university rule?
Applications are limited to students all from the same, single, university.
Teams
How many teams will be selected to participate?
All applications will be reviewed and evaluated by a panel of Amazon experts. Up to ten teams will be selected and sponsored by Amazon. All teams selected in November, 2021 will receive a $250,000 grant while those selected in June, 2022 will receive a $200,000 grant intended to support two full-time students, a month of faculty time, free Alexa devices, and free AWS hosting including access to CPU and GPU based machines, SQL and NoSQL databases, and object storage. See the Official Rules for details.
How many team members can our team have?
There are no minimum or maximum team member requirements. All team members must be enrolled in their university throughout the duration of the competition. All teams will receive a $250,000 grant if selected in November 2021 or a $200,000 grant if selected in June, 2022 regardless of how many members are on the team. We recommend a team with 4-6 students with diverse fields of study or areas of expertise.
Can students from different universities be on the same team?
Teams must be comprised of students attending the same university.
Can one university have more than one team?
Yes, universities may have more than one team.
Can I participate on two separate teams?
You can only be a part of one team for the duration of the competition.
Can undergraduate and graduate students work together?
Yes, teams may be comprised of undergraduate and graduate students.
Do I need a faculty advisor?
All teams must nominate a faculty advisor and include the faculty advisor’s consent in the applications.
What is the role of the faculty advisor?
Faculty advisors will advise students on technical directions and be a sounding board for new ideas, similar to a graduate school advisor. They will also act as the official representative from the university for this competition.
Can we add or remove team members during the competition?
During the competition, faculty advisors may request to remove or add members to the team, subject to approval by Amazon.
Can we discuss our SimBot with faculty or students who aren’t on our team?
Only team members may work on their SimBot. However, the faculty advisor and other students and faculty members at your university may provide support and advice to your team and may co-author technical publications and research papers.
Application process
How do we apply?
Check the SimBot page for the latest update on applications.
What do we need to apply?
Once you have selected your team members, team leader, and faculty sponsor, you are ready to begin the application process.
Do all team members have to apply?
Each team must have a team lead, who should apply on behalf of the whole team. Your application must include all of your team members’ information.
Is there an application fee?
There is no application fee.
How will teams be selected to participate?
All applications will be reviewed by a panel of Amazon employees. Teams will be selected based on the following criteria: (1) the potential scientific contribution to the field; (2) the technical merit of the approach; (3) the novelty of the idea; and (4) an assessment of the team’s ability to execute against their plan. Please be sure to provide enough detail in your application to enable our experts to evaluate your proposal.
Competition details
What is the goal of the challenge?
To develop AI models which advance the state of the art and allow users to naturally interact with a robotic assistant in a virtual world to successfully complete a range of challenges.
How will winners be selected?
Winners will be determined based on the final standings at the completion of the finals period.
Can we use other funding to help us participate in this challenge?
Yes, you may use other funding to support your team, subject to the terms described in the Official Rules. External funding will need to be disclosed by January 1, 2023.
Will Alexa customers be able to engage with our SimBot?
Your team will be required to submit its SimBot for certification and publication by the Amazon Alexa team. After certification, you will enter the Internal Amazon Beta Period, where Amazon employees will test your SimBot and provide feedback. After the Internal Amazon Beta Period, we will allow Amazon Alexa customers to try your SimBot and provide feedback to you. Amazon may impose Availability Criteria, or requirements the SimBot must meet before it will be made available to Alexa users. Availability Criteria may include criteria such as a minimum average customer rating, uptime requirements, and an ability to consistently filter offensive content.
Amazon launched the Echo in the UK, Germany, India, Japan, and other countries. Will localized languages be supported?
Your team must build its SimBot using U.S. English. Your SimBot will be available to Alexa customers in the U.S. Customers in other countries may also access it by setting their Amazon PFM (Preferred Marketplace) to U.S.
Will we publish our research from the Alexa Prize?
Yes. Publishing research papers as an outcome of your work on the Alexa Prize is required for all teams participating in the competition, although teams should not publish Amazon confidential information, as described in the Official Rules. The Alexa Prize requires all teams to submit a technical paper for the Alexa Prize proceedings. Your SimBot will not be selected for the finals if your team does not submit a technical paper for Alexa Prize proceedings. Papers will be published at the end of the competition in an online Proceedings of the Alexa Prize, which will be publicly available.

Teams may also publish research papers in third-party publications and conferences, as long as all papers are provided to Amazon for review at least two weeks before the submission deadlines and no research papers are published before the Alexa Prize proceedings are published without Amazon’s prior approval.
Who will own the intellectual property rights in my submission?
You will retain ownership over your SimBot. Amazon will have a non-exclusive license to any technology or software you develop in connection with the competition. See the Official Rules for details.
Prizes
What are the prizes for winning the competition?
A prize of $500,000 will be awarded to the team that creates the best SimBot. The second-place and third-place finalist teams will receive a $100,000 and a $50,000 prize, respectively. See the contest rules for details.
Do we get a stipend and devices to participate in the Alexa Prize?
Up to ten teams will be sponsored to participate in the Alexa Prize in November, 2021. These teams’ universities will receive a $250,000 research grant to fund the team members’ work over the year. Additional teams selected to participate in the SimBot Live Interaction challenge in June, 2022 will receive a $200,000 research grant to fund the team members’ work over the year.

The sponsorship includes one Alexa-enabled device per team member for up to a total of three devices per team and one Alexa-enabled device per faculty advisor, free AWS services to support the development of their SimBot, and support from the Alexa team.
How can the grant be spent?
The grants will be awarded with the intention that they will support two full-time students for the duration of the Competition and one month of the Faculty Advisor’s salary. No more than 35% of the research grants may be allocated to administrative fees. If your team would like to use the funds in another manner, your faculty advisor must receive approval from Amazon before doing so.
What happens if we are selected and receive a stipend but can no longer participate?
Stipends will be awarded in installments payable to the university. If your team withdraws before any of the installments, remaining funds will not be transferred to the university.
How will the prizes be distributed among a team?
The first, second, and third place prizes will be distributed equally among all registered team members. The official list of registered team members must be confirmed by January 30, 2023.
Timeline
What are the key milestones of the competition?
Teams must submit their applications between October 1, 2021 and October 31, 2021. Between November 1 and November 10, 2021, we will announce teams selected to participate. In the summer of 2022 following the public benchmark phase and the second application period teams will be invited to an Alexa Prize Bootcamp at Amazon where they will receive training on the resources made available to all competing teams. The finals will be scheduled between January 30 and March 27, 2023 and will determine the winning teams in the first annual SimBot Challenge.
If selected, when will we receive the stipend, devices, access to the Alexa Prize SimBot toolkit, our AWS account, and be introduced to our point of contact?
We will reach out to all teams no later than November 10, 2021 with instructions on next steps. Up to ten teams will be selected to receive a $250,000 stipend, Alexa-enabled devices, free AWS services to support their development efforts, and support from the Alexa team.
More information
See the full competition rules or submit your questions. Need assistance? Email: alexaprizesupport@amazon.com

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Principal Applied Scientist, Ads Measurement Science
US, NY, New York
The Measurement Science team in the Measurement, Ad Tech, and Data Science (MADS) organization of Amazon Ads serves a centralized role developing solutions for a multitude of performance measurement products. We create solutions which measure the comprehensive impact of their ad spend, including sales impacts both online and offline and across timescales, and provide actionable insights that enable our advertisers to optimize their media portfolios. We leverage a host of scientific technologies to accomplish this mission, including Generative AI, classical ML, Causal Inference, Natural Language Processing, and Computer Vision. This Principal Applied Scientist leads the technical vision and execution for Amazon Advertising's performance measurement. Our measurement products and tools help customers understand the holistic impact of their spend on Amazon Ads and optimize their portfolios. This is a complex, multi-disciplinary scientific space spanning machine learning, causal inference, statistics and experimentation, natural language processing, and generative AI. As a GenAI-first organization, we build foundational and agentic models that power advertiser use cases across Ads, while empowering our Applied Scientists to directly build and ship products. You will guide a team of scientists with expertise across different domains to come together and innovate on some of the hardest problems in advertising, made more challenging by evolving privacy regulations and technological changes. In measuring the comprehensive impact of advertising, key challenges you will tackle include capturing impact: 1) both for identified and increasingly unidentified web traffic in light of an evolving global privacy landscape; 2) for outcomes across retailers, including both within and beyond Amazon; and 3) for both short- and long-term impacts of advertising. Key job responsibilities * Driving the scientific vision of the teams in your organization and you advise and influence its technical leadership on performance measurement models and products. * Identifying, tackling, and proposing innovative solutions to intrinsically hard, previously unsolved problems. You solve problems pragmatically, applying judgment and experience to balance trade-offs between competing interests. * Bringing clarity to complex problems, probing assumptions, illuminating pitfalls, fostering shared understanding, and guiding towards effective solutions. * Serving and being recognized by internal and external peers as a thought leader in modeled measurement in Ads. You will engage routinely with the broader scientific community, e.g. as a reviewer, program committee member, workshop organizer, or chair at peer-reviewed internal/external conferences. * Leading by example, with your papers, analyses, and code setting the standard in your organization for scientific engineering excellence. * Leading science and design reviews, aligning teams across your organization around coherent algorithmic strategies. * Influencing your team’s science and business strategy by driving one or more team roadmaps contributing to the organization’s roadmap and taking responsibility for some organizational goals. You drive multiple new product features from inception to production launch. * Guiding the career development of others, actively mentoring and educating the larger applied science community on trends, technologies, and best practices. You drive the documentation of scientific innovation. You attract bar-raising talent from academia and industry. * Staying abreast of academic and industry trends, knowing the state of the art, and building on top of existing solutions instead of reinventing when possible. About the team We are a team of scientists across Applied, Research, Data Science and Economist disciplines. You will work with colleagues with deep expertise in ML, NLP, CV, Gen AI, and Causal Inference with a diverse range of backgrounds. We partner closely with top-notch engineers, product managers, sales leaders, and other scientists with expertise in the ads industry and on building scalable modeling and software solutions.
Robotics Applied Scientist
US, CA, Sunnyvale
Amazon is seeking exceptional talent to help develop the next generation of advanced robotics systems that will transform automation at Amazon's scale. We're building robotic systems that combine frontier AI, sophisticated control, and advanced mechanical design to create adaptable automation capable of working safely alongside humans in dynamic environments. This is an opportunity to shape the future of robotics and automation at an unprecedented scale, working with world-class teams pushing the boundaries of what's possible in robotic manipulation, locomotion, and human-robot interaction. We are seeking an Applied Scientist to develop tactile- and force-driven manipulation policies for highly dexterous, multi-fingered robotic hands and grippers. In this role you will research and build policy learning algorithms that enable robotic hands to perform grasping and in-hand manipulation in unstructured, real-world environments, using touch and force feedback as first-class signals rather than afterthoughts. Much of this work is grounded in reinforcement learning. To be successful you need to be highly motivated, dive deep, and deliver to the highest standards. You will demonstrate strong working knowledge of modern policy learning methods, with expertise in taking algorithms from simulation onto real hardware. That means being comfortable working against real physical constraints and treating sim-to-real as a core research problem rather than optimizing for benchmark numbers alone. You will work across tactile signal processing, contact-rich manipulation, sim-to-real transfer, and multi-modal sensor fusion to build robust solutions for autonomous grasping, dexterous re-orientation, and fine motor control. You will bring the desire to learn from new challenges, and the problem-solving and communication skills to work within a highly interactive and experienced team. Key job responsibilities - Design and train manipulation policies that leverage tactile and force feedback for dexterous grasping, in-hand manipulation, and contact-rich tasks, using reinforcement learning, imitation learning, or hybrid approaches. - Drive sim-to-real transfer, closing the gap between simulated and physical performance on real robotic hands. - Shape objectives and control strategies with the hardware in mind, accounting for how motors and actuators actually behave: transmission ratios, torque versus power, backdrivability, and thermal limits. - Build simulation-based and on-robot evaluation frameworks, with benchmarks and metrics that make tactile perception and policy performance systematically comparable across iterations. - Own scientific and technical projects within the tactile sensing and manipulation workstreams, driving from research concept through deployment on physical robotic systems — and, at the senior level, set direction across a workstream. - Collaborate with hardware, mechanical design, firmware, and controls teams — and with partner applied science organizations — to translate research advances into deployable robotic capabilities, and to inform sensor and actuator design decisions with policy-level requirements. - Publish at top-tier venues and build collaborations with the external research community. - Contribute to a strong scientific bar on the team through code and design review, and mentor engineers and interns working on real-world manipulation and sensing problems. A day in the life Your morning might start with a standup alongside hardware and controls engineers reviewing overnight sim-to-real training runs on a multi-finger gripper, debugging why a grasp policy that worked in simulation is slipping on a real sensor array. Mid-morning you join the weekly tactile sensing workstream to align on sensor integration milestones and share early results from a contact-state estimator you have been prototyping. After lunch you spend a focused block iterating on a reinforcement learning reward formulation, testing variations in simulation before queuing runs on the cluster. Later you pair with a mechanical engineer to review sensor placement trade-offs on an upcoming gripper revision, then wrap the day by drafting a short experiment write-up and sketching next steps for a conference submission. No two days look exactly the same: one week you may be collecting teleoperated demonstrations on the physical robot to seed an imitation learning pipeline; the next you could be deep in a codebase refactor to support a new tactile modality. Throughout, you balance hands-on research — writing algorithms, running experiments, analyzing data — with cross-team collaboration and mentoring. The common thread is moving from research insight to working capability on real hardware, with a tight feedback loop between simulation and the physical world. About the team Our is developing next-generation manipulation capabilities for highly dexterous multi-fingered grippers and hands. Our work spans tactile sensor development, manipulation policy learning, and the tight integration of sensing hardware with intelligent control software. We are building systems that can feel, adapt, and manipulate with human-level dexterity. You will join a team working at the frontier of tactile sensing and contact-rich manipulation, helping define how robots perceive and interact with objects through touch. Because we build the hands as well as the policies that drive them, you will have a direct line to the sensor, actuator, and mechanism designs your algorithms depend on — and real influence over how they evolve. This is an opportunity to solve hard problems across perception, learning, and physical interaction alongside a team of scientists and engineers building toward real-world deployment.
Data Scientist, OTS - Data ANCHOR Team
US, TX, Austin
The OTS ANCHOR (Analytics, Insights, and Centralized Hub for OTS Reporting) team is part of the WW IT Operations & RME organization, responsible for delivering data solutions that drive operational excellence across Amazon's global IT infrastructure. We build data pipelines, predictive models, develop analytical intelligence frameworks, and create AI-powered solutions that transform how Amazon manages, triages, and resolves IT operational incidents at scale pointing towards the Letting Data Tell the Story north start vision. We are seeking a Data Scientist to help own the end-to-end data science charter for critical operational workstreams — from forecasting IT service demand and capacity planning to designing intelligent severity triaging models and building the analytical backbone for agentic AI solutions. You will work backwards from complex operational problems to create models and solutions that directly impact the efficiency and reliability of Amazon's IT operations worldwide. Key job responsibilities - Design, develop, and deploy machine learning models for IT operations forecasting, including incident volume prediction, capacity planning, and workforce demand modeling - Build and maintain severity classification and intelligent triaging models that process thousands of daily IT service tickets across global regions - Develop anomaly detection systems to identify emerging patterns in operational data, supporting proactive incident prevention - Apply econometric and statistical methods to measure the impact of operational interventions and inform resource allocation decisions - Partner with engineering teams to productionize ML models via automated pipelines using AWS services (SageMaker, Step Functions, Lambda, Redshift) - Design and conduct experiments to empirically validate model performance and operational impact - Contribute to data quality monitoring frameworks and help maintain standards for operational data integrity - Collaborate with cross-functional teams (ServiceNow platform, Decision Intelligence, Field Operations) to translate analytical insights into actionable recommendations - Communicate findings, model performance, and recommendations to stakeholders and senior leaders through written documents and presentations - Contribute to the team's science roadmap, identifying opportunities to apply ML/AI (including Generative AI) to operational challenges A day in the life Amazon Benefits: Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) Plan
2027 Applied Science Internship - Robotics - United States
US, MA, North Reading
Robotics Applied Scientist II Intern/Co-op (2027) Are you passionate about robotics and research? Do you want to solve real customer problems through innovative technology? Do you enjoy working on scalable research and projects in a collaborative team environment? Do you want to see your science solutions directly impact millions of customers worldwide? We’re looking for current PhD students with a passion for robotic research and applications to join us in 2027 as Robotics Applied Scientist II Interns/Co-ops to shape the future of robotics and transform automation at Amazon’s scale. By applying to this role, you will be considered for Robotics Applied Scientist II Intern/Co-op (2027) opportunities across various Robotics teams at Amazon with different robotics research focus. Internship positions are available for multiple locations, durations (3 to 6+ months), and year-round start dates (winter, spring, summer, fall). Join us at the forefront of Applied Science, where your contributions will shape the future of Robotics! Key job responsibilities As a Robotics Applied Scientist II Intern/Co-op, you will work alongside global experts to advance the state of the art in robotics and artificial intelligence, tackling innovative problems that bridge the gap between research and real-world robotics implementation to innovate and build solutions on behalf of our customers. We are particularly interested in students with specialization and expertise in one or more of the following research areas: - Robotics - Artificial Intelligence - Robotics Manipulation (e.g., robot arm, grasping, dexterous manipulation, end of arm tools/end effector) - Autonomous Mobile Robots - Mobile Manipulation - Multi-Robot Coordination - Autonomous Navigation - Locomotion - Motion/Path Planning - Controls - Perception - Sensing - Robot Learning - Machine Learning - Computer Vision - Large Language Models (LLM), Vision-Language-Action Models (VLA), Vision-Language-Models (VLM) - World Models - Human-Robot Interaction - Robotics Simulation - Optimization - And related! Key responsibilities may include: - Develop novel, scalable algorithms and/or modeling techniques that advance the state-of-the-art in science areas such as robotics, artificial intelligence, or related - Tackle challenging, innovative research problems within robotics, artificial intelligence, or related that bridge the gap between theoretical advancement and practical robotics implementation - Collaborate with cross-functional teams to solve complex problems, and to communicate research findings clearly, leveraging your expertise in robotics, artificial intelligence, or related - Demonstrate the ability to work independently, thrive in a fast-paced, ever-changing environment - Leverage AI-powered tools where applicable to accelerate research, experimentation, and prototyping. - Critically review and validate outputs from AI tools and automated systems. About the team Explore Robotics Teams at Amazon At Amazon, robotics is where innovative research meets real-world deployment. There are many different specialized robotics teams, including the few highlighted below. Learn more about Robotics at Amazon here: https://www.amazon.science/research-areas/robotics Fulfillment Technologies and Robotics We build dynamic partnerships between people and intelligent machines. This intricate collaboration helps Amazon fulfill orders with unmatched accuracy. Working in symphony with our robotic technology, you’ll have the opportunity to extend your technical capabilities by working alongside some of the industry’s most advanced technologies. This includes our fleet of autonomous mobile robots, sophisticated control software, and technologies like language perception, machine learning, object recognition, and semantic understanding of commands. These technologies help us deliver an ever-improving customer and employee experience, as well as improve the safety of our facilities. Amazon Robotics Amazon Robotics is at the epicenter of robotics innovation. We design, test, and build mobile robots and mechatronic systems. Our offices, labs, test floors, and factories are close together, which means we can design the hardware, write the code, test, build, and watch it all come to life. Our areas of focus include advancements in autonomous mobility, AI, robotic management software, and much more. Fauna Fauna is focused on building capable, safe, and genuinely delightful robots for everyday life. Fauna’s goal is simple: make robots people actually want to live and interact with everyday. Fauna develops tightly integrated hardware and software systems that make it faster, safer, and more intuitive to create real-world robotic products. Fauna’s work spans the full stack: mechanical design, control systems, dynamic modeling, and intelligent software. The focus is not just functionality, but overall experience. Amazon Fulfillment Technologies Amazon Fulfillment Technologies develops tech solutions that create network optimizations for all Amazon sites worldwide. We own network infrastructure and devices in all buildings and labor planning and scheduling technology for fulfillment centers in North America and Europe.
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