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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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Applied Scientist, Superconducting Digital and Cryogenic Control Electronics,Center for Quantum Computing, Physical Design and Simulation, Enabling Technologies
US, CA, San Francisco
The Amazon Center for Quantum Computing (CQC) is seeking an Applied Scientist to research and design cryogenic control hardware for large-scale quantum processors, with an emphasis on superconducting digital circuits. Controlling and reading out orders of magnitude more qubits than today's systems demands rethinking where classical control lives and what technology implements it; you will design and model superconducting digital logic (e.g., single-flux-quantum-family circuits) and related cryogenic electronics, evaluate them against the wiring, power, and thermal budgets of a scaled system, and co-design control approaches with the qubit devices they serve. You will carry designs from concept through simulation, layout, design review, and fabrication handoff, and your evaluations will inform which control-electronics directions the organization invests in. Key job responsibilities • Design and simulate superconducting digital circuits and cryogenic control/readout electronics for scalable qubit control • Develop and validate Josephson-junction circuit models, timing and margin analyses, and verification methodology for superconducting digital designs • Quantify system-level trade-offs — wiring count, power dissipation at each cryogenic stage, latency, footprint — across candidate control architectures, and communicate recommendations • Co-design control interfaces with qubit-device colleagues so control electronics and quantum devices are developed as one system • Deliver design artifacts through the organization's design-request and design-review processes, including tapeout-ready layouts and verification reports • Present results internally and, where appropriate, publish in peer-reviewed venues About the team The Enabling Technologies team develops technologies and relationships facilitating scaling, including alternative quantum processor architectures, superconducting qubit device packaging, and cryogenic control device electronics. We work alongside a co-located quantum processor design team focused on current-generation devices; the two teams share design and review processes, and moving ideas between them is an explicit part of our charter.
Satellite GNC Engineer, Amazon Leo
US, WA, Redmond
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The code that flies is the code you write. - Solve hard problems in precise pointing, payload cueing and fleet autonomy. - Work across design, simulation, test and flight operations, not a narrow slice of the lifecycle. **Export Control Requirement:** Due to applicable export control laws and regulations, candidates must be a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum. Key job responsibilities - Design and analyze algorithms for state estimation, attitude determination and control, precise pointing and payload cueing against demanding performance requirements. - Implement these algorithms in production C++ flight software. Our GNC engineers own their algorithms all the way into flight, and partner with our embedded software engineers to integrate and test them. - Write concepts of operations for each phase of a satellite's life, from launch and orbit raising to service and deorbit, including failures and recovery. Balance what the payload needs against momentum, power, thermal and ground-contact limits. - Develop momentum management strategies with reaction wheels and magnetic torquers. Help select, size and place the GNC sensors and actuators for future satellites, and design the algorithms that use them. These include star trackers, magnetometers, sun sensors, IMUs and GNSS receivers. - Develop onboard autonomy, including Fault Detection, Isolation and Recovery (FDIR), so that the fleet operates safely at scale with minimal ground intervention. - Build and validate satellite and constellation models and simulations at several levels of fidelity, including 6-DOF simulation and Monte Carlo analysis. Verify closed-loop performance in hardware-in-the-loop (HITL) tests. - Support component environmental tests, functional and performance checkout, and subsystem and satellite integration in our labs. - Analyze telemetry from the whole fleet. Build the metrics, dashboards and tools that track pointing performance and payload operations time as the constellation grows, and use them to improve the fleet. - Operate the GNC system on orbit and take part in the team's on-call rotation. Review fleet data, support maneuvers, and resolve anomalies when on-orbit behavior differs from the ground model. - Review designs and code with the team, and document your algorithms, analyses and results clearly. A day in the life This role covers a wide range of problems across the spacecraft and the network. You will derive and prototype estimation and control algorithms, and then turn them into production flight code. You will prove them in 6-DOF and Monte Carlo simulation and in hardware-in-the-loop tests in the lab. You will support satellite integration. When a satellite does not behave as the ground model predicted, you will dig into fleet telemetry, find the cause and drive the fix. You will own each problem end to end, with the focus to go deep on it. GNC is at the center of safe flight, so you will work across the whole program. The payload, power, thermal and operations teams all depend on GNC, and you will balance their needs against the pointing and momentum budgets. You will partner closely with avionics, flight software and embedded software engineers to make your algorithms run reliably on the spacecraft. You will help the mechanical teams shape the next generation of satellite hardware, from reaction wheels to star trackers. As satellites move from design through manufacturing into orbit, you will work with systems engineering and Assembly, Integration and Test. The problems are hard: tight pointing requirements, a large constellation to keep flying safely, and the chance to invent capabilities that do not exist yet. Constant work with other teams makes this a place where you keep learning and growing. About the team You will join the Satellite Attitude Determination and Control team. We own GNC for our satellites end to end: algorithm design, flight software, lab integration, and flight operations of our own satellites on orbit. Our engineers bring deep experience from many satellite programs and other flight vehicles, with real strength in both our mission and the core GNC disciplines. We design, prototype, test, iterate and learn together. Because GNC is central to safe flight, we drive the concepts of operations and many of the system-level analyses on the program. We also have a lot of freedom. We trust our engineers to choose their own tools and approaches for the problems they face, and to own the results. If you want the autonomy to solve hard problems your way, with a team of strong engineers, you will feel at home here.
Senior Satellite GNC Engineer, Amazon Leo
US, WA, Redmond
Amazon Leo is building a constellation of thousands of low Earth orbit satellites. It will bring fast, reliable internet to customers beyond the reach of existing networks. On the Guidance, Navigation and Control (GNC) team, you will design the algorithms, simulations and onboard autonomy that keep every satellite precisely pointed and stable. Your work lets the payload serve customers on the ground, and it keeps the fleet flying safely. This is satellite GNC at constellation scale. The constellation is launching and growing today, so you will see your work go from concept to orbit, and then fly on many satellites. In this role, you will: - Take your GNC algorithms from concept to orbit, and stay with them through integration, test and on-orbit operations. - Write the production C++ flight code for your own algorithms. The code that flies is the code you write. - Solve hard problems in precise pointing, payload cueing and fleet autonomy. - Work across design, simulation, test and flight operations, not a narrow slice of the lifecycle. **Export Control Requirement:** Due to applicable export control laws and regulations, candidates must be a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum. Key job responsibilities - Design and analyze algorithms for state estimation, attitude determination and control, precise pointing and payload cueing against demanding performance requirements. - Implement these algorithms in production C++ flight software. Our GNC engineers own their algorithms all the way into flight, and partner with our embedded software engineers to integrate and test them. - Write concepts of operations for each phase of a satellite's life, from launch and orbit raising to service and deorbit, including failures and recovery. Balance what the payload needs against momentum, power, thermal and ground-contact limits. - Develop momentum management strategies with reaction wheels and magnetic torquers. Help select, size and place the GNC sensors and actuators for future satellites, and design the algorithms that use them. These include star trackers, magnetometers, sun sensors, IMUs and GNSS receivers. - Develop onboard autonomy, including Fault Detection, Isolation and Recovery (FDIR), so that the fleet operates safely at scale with minimal ground intervention. - Build and validate satellite and constellation models and simulations at several levels of fidelity, including 6-DOF simulation and Monte Carlo analysis. Verify closed-loop performance in hardware-in-the-loop (HITL) tests. - Support component environmental tests, functional and performance checkout, and subsystem and satellite integration in our labs. - Analyze telemetry from the whole fleet. Build the metrics, dashboards and tools that track pointing performance and payload operations time as the constellation grows, and use them to improve the fleet. - Operate the GNC system on orbit and take part in the team's on-call rotation. Review fleet data, support maneuvers, and resolve anomalies when on-orbit behavior differs from the ground model. - Review designs and code with the team, and document your algorithms, analyses and results clearly. A day in the life This role covers a wide range of problems across the spacecraft and the network. You will derive and prototype estimation and control algorithms, and then turn them into production flight code. You will prove them in 6-DOF and Monte Carlo simulation and in hardware-in-the-loop tests in the lab. You will support satellite integration. When a satellite does not behave as the ground model predicted, you will dig into fleet telemetry, find the cause and drive the fix. You will own each problem end to end, with the focus to go deep on it. GNC is at the center of safe flight, so you will work across the whole program. The payload, power, thermal and operations teams all depend on GNC, and you will balance their needs against the pointing and momentum budgets. You will partner closely with avionics, flight software and embedded software engineers to make your algorithms run reliably on the spacecraft. You will help the mechanical teams shape the next generation of satellite hardware, from reaction wheels to star trackers. As satellites move from design through manufacturing into orbit, you will work with systems engineering and Assembly, Integration and Test. The problems are hard: tight pointing requirements, a large constellation to keep flying safely, and the chance to invent capabilities that do not exist yet. Constant work with other teams makes this a place where you keep learning and growing. About the team You will join the Satellite Attitude Determination and Control team. We own GNC for our satellites end to end: algorithm design, flight software, lab integration, and flight operations of our own satellites on orbit. Our engineers bring deep experience from many satellite programs and other flight vehicles, with real strength in both our mission and the core GNC disciplines. We design, prototype, test, iterate and learn together. Because GNC is central to safe flight, we drive the concepts of operations and many of the system-level analyses on the program. We also have a lot of freedom. We trust our engineers to choose their own tools and approaches for the problems they face, and to own the results. If you want the autonomy to solve hard problems your way, with a team of strong engineers, you will feel at home here.
Applied Science III
US, WA, Seattle
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Applied Scientist, Sponsored Products and Brands
US, NY, New York
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Applied Scientist II, AWS Applied Data Science Labs
US, WA, Seattle
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Applied Scientist III - AMZ10037670
US, WA, Seattle
MULTIPLE POSITIONS AVAILABLE Employer: AMAZON.COM SERVICES LLC Offered Position: Applied Scientist III Job Location: Seattle, Washington Job Number: AMZ10037670 Position Responsibilities: Participate in the design, development, evaluation, deployment and updating of data-driven models and analytical solutions for machine learning (ML) and/or natural language (NL) applications. Develop and/or apply statistical modeling techniques (e.g. Bayesian models and deep neural networks), optimization methods, and other ML techniques to different applications in business and engineering. Routinely build and deploy ML models on available data, and run and analyze experiments in a production environment. Identify new opportunities for research in order to meet business goals. Research and implement novel ML and statistical approaches to add value to the business. Mentor junior engineers and scientists. Position Requirements: Master’s degree or foreign equivalent degree in Computer Science, Machine Learning, Engineering, or a related field and two years of research or work experience in the job offered, or as a Research Scientist, Research Assistant, Software Engineer, or a related occupation. Employer will accept a Bachelor’s degree or foreign equivalent degree in Computer Science, Machine Learning, Engineering, or a related field and five years of progressive post-baccalaureate research or work experience in the job offered or a related occupation as equivalent to the Master’s degree and two years of research or work experience. Must have one year of research or work experience in the following skill(s): (1) programming in Java, C++, Python, or equivalent programming language; and (2) conducting the analysis and development of various supervised and unsupervised machine learning models for moderately complex projects in business, science, or engineering. Amazon.com is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation. 40 hours / week, 8:00am-5:00pm, Salary Range $167,100/year to $226,100/year. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, visit: https://www.aboutamazon.com/workplace/employee-benefits. #0000
Applied Scientist, PXT Central Science
US, CA, San Francisco
The Central Science Team within Amazon’s People Experience and Technology org (PXTCS) uses economics, behavioral science, statistics, and machine learning to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives, well-being, and the value of work to Amazonians. We are an interdisciplinary team, which combines the talents of science and engineering to develop and deliver solutions that measurably achieve this goal. We are looking for an Applied Scientist to build production machine learning solutions that improve employee experiences and inform workforce decisions. You will work on problems spanning predictive modeling, natural language processing, recommendation systems, personalization, generative AI, and causal evaluation. These solutions will predict workforce outcomes, identify individual and organizational needs, recommend targeted actions, and measure the causal impact of programs, products, and policies across diverse employee populations and business contexts. As an Applied Scientist, you will develop models and algorithms from prototype through production. You will collaborate with other scientists and economists to combine machine learning with causal inference and experimentation, allowing teams to understand both what is likely to happen and which actions will improve outcomes. You will also work with product managers, engineers, and business partners to translate business needs into technical solutions and communicate methods and results to technical and nontechnical audiences. Key job responsibilities • Design, develop, and deploy machine learning solutions in production environments. • Develop solutions using techniques that include predictive modeling, deep learning, natural language processing, recommendation systems, personalization, and generative AI. • Build models that predict workforce outcomes, identify employee and organizational needs, and recommend targeted actions. • Partner with economists and other scientists to design causal evaluations and experimental frameworks that measure the impact of programs, products, and policies. • Combine predictive models with causal estimates to help business partners identify effective actions and make evidence-based decisions. • Collaborate with product managers, engineers, and business partners to translate business requirements into modeling approaches and contribute to technical design and roadmap decisions. • Evaluate model accuracy, performance, calibration, and limitations, and identify opportunities for improvement. • Communicate technical concepts, methods, results, and recommendations to technical peers and business partners. A day in the life • Analyze data to investigate model performance or understand an unexpected result from a causal evaluation. • Brainstorm modeling and evaluation approaches with applied scientists and economists on the team. • Develop and test model features, recommendation methods, or generative AI applications. • Design or analyze experiments and observational studies to estimate the causal impact of programs, products, or policies. • Run simulations, offline evaluations, or backtests to assess model performance. • Meet with product, engineering, and business partners to review requirements, data, designs, and implementation decisions. • Review code changes or technical design documents from scientists and engineers. • Write and present documents covering methods, results, limitations, and recommendations. About the team The People eXperience and Technology Central Science Team (PXTCS) uses economics, behavioral science, statistics, and machine learning to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives, wellbeing, and the value of work to Amazonians. We are an interdisciplinary team that combines the talents of science and engineering to develop and deliver solutions that measurably achieve this goal.
Applied Scientist II, Detail Page
IN, KA, Bengaluru
Amazon.com’s Product Detail Page team is looking for talented, motivated and passionate applied scientist to be part of the design and development of a highly scalable multi-tiered shopping application to provide the best possible online shopping experience for Amazon customers world-wide. Our team is comprised of talented applied scientists, developers, testers, program managers, designers and product managers tasked with the singular goal to create THE world's best buying experience. Scientists on this team develop the next-generation technologies and experiences that change how millions interact and shop online. To provide the best possible online shopping at the scale of the web requires ideas from every area of computer science, including distributed computing, large-scale system design, machine learning, natural language processing, data compression and user interface design; the list goes on and is growing every day. We need our scientists to be versatile and always eager to tackle new problems as we continue to push technology forward. Our team leverages sophisticated econometric, machine learning, and big data technologies to help customers to discover the right products at the right prices from millions of trusted sellers billions of times a day. If you are looking for a career-defining opportunity on one of the most customer centric and business impacting teams within Amazon, we’d love to hear from you. We are looking for an Applied Scientist to help build the next generation of Detail Page optimization algorithms. These new set of algorithms will incorporate the continually changing preferences of our customers and continue to scale with numerous new programs that Amazon is introducing for our customers. You will work with multiple Amazon businesses and programs to identify big business opportunities and propose new business features and technical systems to improve customer experience on Amazon Detail Page, Search Page and many other widgets throughout the website. You will be responsible for the quality of algorithm design and will get the opportunity to present your ideas and share results of your deliverables with Amazon executives on a frequent basis. You will get an opportunity to work with senior scientists to define and enforce broad, company-wide technical standards in optimization techniques, statistical modeling and simulation techniques, and/or data analytics.
Applied Scientist I, Tablet Product Software
US, WA, Seattle
Are you excited to play a strategic role in defining the customer experience on Tablets? Come join a dynamic, customer-obsessed, world-class science team to completely reshape the customer experience on our tablets. Key job responsibilities Using Amazon’s large-scale computing resources, you will design and deploy state-of-the-art recommendation models. You will ask research questions about customer behavior, design state-of-the-art models that help customers discover content, and deploy these models to production alongside other engineers. You will participate in the Amazon ML community and mentor other engineers with a strong interest in and knowledge of ML and generative AI. Your work will directly benefit customers! A day in the life We are looking for a passionate, hard-working, and talented Applied Scientist who has experience developing state-of-the-art models and deploying them to production. You will have an opportunity to make an enormous impact on the design, architecture, and implementation of products used everyday by real customers! About the team The Alexa Tablet team is a world-class team that delivers high-quality, innovative products that are loved by our customers. Our team focuses on spinning many of Amazon’s flywheels with bar-raising mobile experiences on our tablets. Over the last 12 years, we have built 4.0+ star rated products, and we continue to look for ways to scale our business. Join us as we continue our ambitious journey which will give you the opportunity to deliver disruptive products with global impact.
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