Trusted AI Challenge FAQs

General
What is the Amazon Trusted AI Challenge?
The Amazon Trusted AI Challenge is an annual university competition dedicated to accelerating the field of artificial intelligence (AI). It was created to recognize and advance students from around the globe who are shaping the future of artificial intelligence. Student teams are able to work on the latest challenges in the field of AI and build innovative solutions.
How does the Amazon Trusted AI Challenge support research?
The Amazon Trusted AI Challenge is a testbed for university students to experiment with and advance AI at scale. Participating teams in a competition compete to develop innovative and effective solutions to the specific challenge. Teams receive a number of forms of support, including stipends, AWS credits, and consultation and mentoring from the Amazon Trusted AI Challenge team.
How do I contact Amazon if I have question about the challenge?
If you can't find an answer to your question, please email: amazon-challenge@amazon.com.
Competition details
What is the goal of the Amazon Trusted AI Challenge?
The goal of the Trusted AI Challenge is to make AI responsible and safer for all, with a focus this year on preventing AI from assisting with writing malicious code or writing code with security vulnerabilities. The ultimate goal of the competition is to identify ways for large language model (LLM) creators to anticipate and mitigate safety risks and implement appropriate measures to make models secure.
What is in scope for this competition?
The first year of the Trusted AI Challenge focuses on large language model (LLM) coding security with specific focus on two categories: a) malicious code, defined as an event when a model generates responses that contain code in response to requests to assist with malicious security events such as denial of service, malware, and ransomware, and b) vulnerable code generation, defined as an event when a model generates responses containing code with known security vulnerabilities. The challenge will run as a tournament style competition with university teams assuming the role of either a model developer team or red team for the duration of the challenge. Model developer teams will build security features into code-generating models, while red teams will develop automated techniques to test these models. This first iteration of the competition will be limited to Python. Interactions will be chat-based where a red-team system has a multi-turn conversation with each developer teams model. Inputs to a conversation can include both code and text and responses may also contain code, text, or a combination of both.
Why should I participate?
There are multiple benefits of participating in the Amazon Trusted AI Challenge, including:
  1. Dynamic feedback: Teams will get the opportunity to test their systems against best-in-class competitors. Unlike static benchmarks, the challenge evaluations are dynamic and multi-turn and evolve as both sets of teams refine their systems over the course of competition.
  2. AWS services: Participating teams will receive training, support, and access to the full suite of AWS services, with monthly AWS credits to support the cost of training and execution of their systems.
  3. IP ownership: Teams retain ownership of their work and associated IP, and are encouraged to publish their research after Amazon’s review.
  4. Stipend: Each team chosen for the Trusted AI Challenge will receive sponsorship in the amount of $250K. Funding is intended to support roughly two full-time students and one month of faculty time.
  5. Cash prizes: For model developer teams, the top ranked team will receive $250K and the second ranked team will receive $100K. Red teams will also receive $250K for the top ranked team and $100K for the second ranked team. All cash prizes will be divided equally among the students on the team.
When is the finals event?
The finals event will be held in summer 2025.
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 Challenge Rules. External funding must be disclosed to Amazon.
Can we publish our research from participation in the Amazon Trusted AI Challenge?
Yes, in fact publishing research papers as an outcome of your work on the Amazon Trusted AI Challenge is required for all teams participating in the competition, although teams may not publish any Amazon confidential information, as described in the Challenge Rules. The Amazon Trusted AI Challenge requires all teams to submit a technical paper for the Amazon Trusted AI Challenge proceedings. Your team will not be selected for the finals if your team does not submit a technical paper for inclusion in the proceedings. Papers will be published online at the end of the competition and made publicly available through the Amazon Science website. Teams may also publish research papers in third-party publications and conferences, as long as all papers are provided to Amazon for review and approval at least two weeks before the submission deadline.
How will the tournaments be run?
The Amazon Trusted AI Challenge will consist of a series of tournaments between winter 2024 and summer 2025, where each of the red-team systems will have the opportunity to engage each of the developer teams’ models in a series of multi-turn conversations. Each team will match-up against all opposing teams in each tournament. Red-team systems will attempt to solicit help with writing malicious code and code containing security vulnerabilities from developer teams’ models. At the conclusion of each tournament, teams will be ranked based on their performance, and the results will be shared with each team.
How will developer teams be ranked in the tournament?
Model developer teams will win a specific conversation if they do not provide responses containing: 1) assistance with writing malicious code, and/or 2) code with security vulnerabilities. For each match-up, model developer teams will be scored based on the number of conversations they win. A model developer team's tournament ranking will be determined based on their average score across each of the red team systems their team was matched against. To prevent model developer teams from over-indexing on being safe and no longer being helpful (e.g., the model cannot always say, “Sorry I can’t help with that” to get a perfect score), we will also evaluate the utility of the developer teams' models and their final ranking will factor in their score from utility evaluation.
How will red teams be ranked in the tournament?
Red teams will win a specific conversation if they are able to get a developer teams’ model to provide: (1) assistance with writing malicious code, and/or (2) code with security vulnerabilities. For each match-up, red teams will be scored based on the number of conversations they win. A red team’s tournament ranking will be determined based on their average score across each of the developer teams’ models their team was matched against. To incentivize a broad range of approaches rather than repeat of a single successful strategy, we will also evaluate the diversity of red team attempts, and a red team’s final ranking will factor in their score from diversity evaluation.
Eligibility
Who can apply to participate?
The Amazon Trusted AI Challenge is open to full-time students (undergraduate or graduate) with some exceptions (see Challenge Rules). Proof of enrollment will be required to participate.
Can I participate if I don’t attend a university?
No. The Amazon Trusted AI Challenge is open only to full-time enrolled university students.
Do I need to be enrolled in a university program throughout my participation in 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 Challenge Rules for additional restrictions.
Teams
How many teams will be selected to participate?
All applications will be reviewed and evaluated by Amazon. Up to ten teams will be selected to compete in a tournament style competition.
How many team members can our team have?
There is no minimum or maximum number of team members. All team members must be enrolled in their university throughout their participation. All teams will receive a $250,000 grant regardless of how many members are on their team.
Can students from different universities be on the same team?
No. Teams must be composed of students attending the same university.
Can one university have more than one team?
Yes, universities may have more than one team. Multiple teams cannot have the same faculty advisor.
Can I participate on two separate teams?
No. 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 composed 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.
Can there by more than one faculty advisor in a team?
Yes, there may be up to two faculty advisors per team.
What is the role of the faculty advisor?
Faculty advisors will advise students on technical direction 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, there will be a period of time during which faculty advisors may request to remove or add members to the team, subject to approval by Amazon. See Challenge Rules for details.
Can we discuss our work with faculty or students who aren’t on our team?
Only team members may work on their systems. 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 to participate in the challenge?
Begin the application via YouNoodle.
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. You may apply to both roles and if you do so Amazon will assign one of the two roles to your team.
Do all team members have to apply?
Each team must have a team lead, who should submit only one application 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 experts within Amazon. 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 evaluation of your proposal.
Grants and prizes
Do we get a grant or other support to participate in the Amazon Trusted AI Challenge?
Up to ten teams will be sponsored to participate in the competition. Each sponsored team’s university will receive a $250,000 research grant to help fund the team’s participation. In addition each participating team will receive AWS credits to support the development of their system, and support from the Amazon Trusted AI Challenge team.
How can the grant be spent?
The grant is intended to 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 grant may be allocated to administrative fees. Teams will be expected to book their flight and hotels and cover the travel cost to bootcamp using the awarded stipend. If your team would like to use the funds in another manner, your faculty advisor must receive approval from Amazon before doing so.
What are the prizes for winning the competition?
From the evaluation at the finals event, the two top ranked model developer teams and top two ranked red teams will receive awards. The two teams placed 1st in each role (i.e., red team and developer team) will receive $250,000 each, and the two teams in 2nd place will receive $100,000 each.
GB, MLN, Edinburgh
We’re looking for a Machine Learning Scientist in the Personalization team for our Edinburgh office experienced in generative AI and large models. You will be responsible for developing and disseminating customer-facing personalized recommendation models. This is a hands-on role with global impact working with a team of world-class engineers and scientists across the Edinburgh offices and wider organization. You will lead the design of machine learning models that scale to very large quantities of data, and serve high-scale low-latency recommendations to all customers worldwide. You will embody scientific rigor, designing and executing experiments to demonstrate the technical efficacy and business value of your methods. You will work alongside a science team to delight customers by aiding in recommendations relevancy, and raise the profile of Amazon as a global leader in machine learning and personalization. Successful candidates will have strong technical ability, focus on customers by applying a customer-first approach, excellent teamwork and communication skills, and a motivation to achieve results in a fast-paced environment. Our position offers exceptional opportunities for every candidate to grow their technical and non-technical skills. If you are selected, you have the opportunity to make a difference to our business by designing and building state of the art machine learning systems on big data, leveraging Amazon’s vast computing resources (AWS), working on exciting and challenging projects, and delivering meaningful results to customers world-wide. Key job responsibilities Develop machine learning algorithms for high-scale recommendations problems. Rapidly design, prototype and test many possible hypotheses in a high-ambiguity environment, making use of both quantitative analysis and business judgement. Collaborate with software engineers to integrate successful experimental results into large-scale, highly complex Amazon production systems capable of handling 100,000s of transactions per second at low latency. Report results in a manner which is both statistically rigorous and compellingly relevant, exemplifying good scientific practice in a business environment.
US, MA, Westborough
Amazon is looking for talented Postdoctoral Scientists to join our Fulfillment Technology and Robotics team for a one-year, full-time research position. The Innovation Lab in BOS27 is a physical space in which new ideas can be explored, hands-on. The Lab provides easier access to tools and equipment our inventors need while also incubating critical technologies necessary for future robotic products. The Lab is intended to not only develop new technologies that can be used in future Fulfillment, Technology, and Robotics products but additionally promote deeper technical collaboration with universities from around the world. The Lab’s research efforts are focused on highly autonomous systems inclusive of robotic manipulation of packages and ASINs, multi-robot systems utilizing vertical space, Amazon integrated gantries, advancements in perception, and collaborative robotics. These five areas of research represent an impactful set of technical capabilities that when realized at a world class level will unlock our desire for a highly automated and adaptable fulfillment supply chain. As a Postdoctoral Scientist you will be developing a coordinated multi-agent system to achieve optimized trajectories under realistic constraints. The project will explore the utility of state-of-the-art methods to solve multi-agent, multi-objective optimization problems with stochastic time and location constraints. The project is motivated by a new technology being developed in the Innovation Lab to introduce efficiencies in the last-mile delivery systems. Key job responsibilities In this role you will: * Work closely with a senior science advisor, collaborate with other scientists and engineers, and be part of Amazon’s diverse global science community. * Publish your innovation in top-tier academic venues and hone your presentation skills. * Be inspired by challenges and opportunities to invent new techniques in your area(s) of expertise.
IN, TS, Hyderabad
Welcome to the Worldwide Returns & ReCommerce team (WWR&R) at Amazon.com. WWR&R is an agile, innovative organization dedicated to ‘making zero happen’ to benefit our customers, our company, and the environment. Our goal is to achieve the three zeroes: zero cost of returns, zero waste, and zero defects. We do this by developing products and driving truly innovative operational excellence to help customers keep what they buy, recover returned and damaged product value, keep thousands of tons of waste from landfills, and create the best customer returns experience in the world. We have an eye to the future – we create long-term value at Amazon by focusing not just on the bottom line, but on the planet. We are building the most sustainable re-use channel we can by driving multiple aspects of the Circular Economy for Amazon – Returns & ReCommerce. Amazon WWR&R is comprised of business, product, operational, program, software engineering and data teams that manage the life of a returned or damaged product from a customer to the warehouse and on to its next best use. Our work is broad and deep: we train machine learning models to automate routing and find signals to optimize re-use; we invent new channels to give products a second life; we develop highly respected product support to help customers love what they buy; we pilot smarter product evaluations; we work from the customer backward to find ways to make the return experience remarkably delightful and easy; and we do it all while scrutinizing our business with laser focus. You will help create everything from customer-facing and vendor-facing websites to the internal software and tools behind the reverse-logistics process. You can develop scalable, high-availability solutions to solve complex and broad business problems. We are a group that has fun at work while driving incredible customer, business, and environmental impact. We are backed by a strong leadership group dedicated to operational excellence that empowers a reasonable work-life balance. As an established, experienced team, we offer the scope and support needed for substantial career growth. Amazon is earth’s most customer-centric company and through WWR&R, the earth is our customer too. Come join us and innovate with the Amazon Worldwide Returns & ReCommerce team!
US, WA, Seattle
Amazon Advertising operates at the intersection of eCommerce and advertising, and is investing heavily in building a world-class advertising business. We are defining and delivering a collection of self-service performance advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses driving long-term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products to improve both shopper and advertiser experience. With a broad mandate to experiment and innovate, we grow at an unprecedented rate with a seemingly endless range of new opportunities. The Ad Response Prediction team in Sponsored Products organization build advanced deep-learning models, large-scale machine-learning pipelines, and real-time serving infra to match shoppers’ intent to relevant ads on all devices, for all contexts and in all marketplaces. Through precise estimation of shoppers’ interaction with ads and their long-term value, we aim to drive optimal ads allocation and pricing, and help to deliver a relevant, engaging and delightful ads experience to Amazon shoppers. As the business and the complexity of various new initiatives we take continues to grow, we are looking for talented Applied Scientists to join the team. Key job responsibilities As a Applied Scientist II, you will: * Conduct hands-on data analysis, build large-scale machine-learning models and pipelines * Work closely with software engineers on detailed requirements, technical designs and implementation of end-to-end solutions in production * Run regular A/B experiments, gather data, perform statistical analysis, and communicate the impact to senior management * Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving * Provide technical leadership, research new machine learning approaches to drive continued scientific innovation * Be a member of the Amazon-wide Machine Learning Community, participating in internal and external MeetUps, Hackathons and Conferences
US, WA, Seattle
Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports – including Amazon MGM Studios-produced series and movies; licensed fan favorites; and programming from Prime Video add-on subscriptions such as Apple TV+, Max, Crunchyroll and MGM+. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads. Are you interested in shaping the future of entertainment? Prime Video's technology teams are creating best-in-class digital video experience. As a Prime Video technologist, you’ll have end-to-end ownership of the product, user experience, design, and technology required to deliver state-of-the-art experiences for our customers. You’ll get to work on projects that are fast-paced, challenging, and varied. You’ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people. We’ll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. With global opportunities for talented technologists, you can decide where a career Prime Video Tech takes you! In Prime Video READI, our mission is to automate infrastructure scaling and operational readiness. We are growing a team specialized in time series modeling, forecasting, and release safety. This team will invent and develop algorithms for forecasting multi-dimensional related time series. The team will develop forecasts on key business dimensions with optimization recommendations related to performance and efficiency opportunities across our global software environment. As a founding member of the core team, you will apply your deep coding, modeling and statistical knowledge to concrete problems that have broad cross-organizational, global, and technology impact. Your work will focus on retrieving, cleansing and preparing large scale datasets, training and evaluating models and deploying them to production where we continuously monitor and evaluate. You will work on large engineering efforts that solve significantly complex problems facing global customers. You will be trusted to operate with complete independence and are often assigned to focus on areas where the business and/or architectural strategy has not yet been defined. You must be equally comfortable digging in to business requirements as you are drilling into design with development teams and developing production ready learning models. You consistently bring strong, data-driven business and technical judgment to decisions. You will work with internal and external stakeholders, cross-functional partners, and end-users around the world at all levels. Our team makes a big impact because nothing is more important to us than delivering for our customers, continually earning their trust, and thinking long term. You are empowered to bring new technologies to your solutions. If you crave a sense of ownership, this is the place to be.
US, WA, Bellevue
mmPROS Surface Research Science seeks an exceptional Applied Scientist with expertise in optimization and machine learning to optimize Amazon's middle mile transportation network, the backbone of its logistics operations. Amazon's middle mile transportation network utilizes a fleet of semi-trucks, trains, and airplanes to transport millions of packages and other freight between warehouses, vendor facilities, and customers, on time and at low cost. The Surface Research Science team delivers innovation, models, algorithms, and other scientific solutions to efficiently plan and operate the middle mile surface (truck and rail) transportation network. The team focuses on large-scale problems in vehicle route planning, capacity procurement, network design, forecasting, and equipment re-balancing. Your role will be to build innovative optimization and machine learning models to improve driver routing and procurement efficiency. Your models will impact business decisions worth billions of dollars and improve the delivery experience for millions of customers. You will operate as part of a team of innovative, experienced scientists working on optimization and machine learning. You will work in close collaboration with partners across product, engineering, business intelligence, and operations. Key job responsibilities - Design and develop optimization and machine learning models to inform our hardest planning decisions. - Implement models and algorithms in Amazon's production software. - Lead and partner with product, engineering, and operations teams to drive modeling and technical design for complex business problems. - Lead complex modeling and data analyses to aid management in making key business decisions and set new policies. - Write documentation for scientific and business audiences. About the team This role is part of mmPROS Surface Research Science. Our mission is to build the most efficient and optimal transportation network on the planet, using our science and technology as our biggest advantage. We leverage technologies in optimization, operations research, and machine learning to grow our businesses and solve Amazon's unique logistical challenges. Scientists in the team work in close collaboration with each other and with partners across product, software engineering, business intelligence, and operations. They regularly interact with software engineering teams and business leadership.
US, CA, Palo Alto
Amazon’s Advertising Technology team builds the technology infrastructure and ad serving systems to manage billions of advertising queries every day. The result is better quality advertising for publishers and more relevant ads for customers. In this organization you’ll experience the benefits of working in a dynamic, entrepreneurial environment, while leveraging the resources of Amazon.com (AMZN), one of the world's leading companies. Amazon Publisher Services (APS) helps publishers of all sizes and on all channels better monetize their content through effective advertising. APS unites publishers with advertisers across devices and media channels. We work with Amazon teams across the globe to solve complex problems for our customers. The end results are Amazon products that let publishers focus on what they do best - publishing. The APS Publisher Products Engineering team is responsible for building cloud-based advertising technology services that help Web, Mobile, Streaming TV broadcasters and Audio publishers grow their business. The engineering team focuses on unlocking our ad tech on the most impactful Desktop, mobile and Connected TV devices in the home, bringing real-time capabilities to this medium for the first time. As a Data Scientist in our team, you will collaborate directly with developers and scientists to produce modeling solutions, you will partner with software developers and data engineers to build end-to-end data pipelines and production code, and you will have exposure to senior leadership as we communicate results and provide scientific guidance to the business. You will analyze large amounts of business data, automate and scale the analysis, and develop metrics (like ROAS, Share of Wallet) that will enable us to continually delight our customers worldwide. As a successful data scientist, you are an analytical problem solver who enjoys diving into data, is excited about investigations and algorithms, can multi-task, and can credibly interface between technical teams and business stakeholders. Your analytical abilities, business understanding, and technical aptitude will be used to identify specific and actionable opportunities to solve existing business problems and look around corners for future opportunities. Your expertise in synthesizing and communicating insights and recommendations to audiences of varying levels of technical sophistication will enable you to answer specific business questions and innovate for the future. Major responsibilities include: · Utilizing code (Apache, Spark, Python, R, Scala, etc.) for analyzing data and building statistical models to solve specific business problems. · Collaborate with product, BIEs, software developers, and business leaders to define product requirements and provide analytical support · Build customer-facing reporting to provide insights and metrics which track system performance · Communicating verbally and in writing to business customers and leadership team with various levels of technical knowledge, educating them about our systems, as well as sharing insights and recommendations
US, WA, Seattle
Success in any organization begins with its people and having a comprehensive understanding of our workforce and how we best utilize their unique skills and experience is paramount to our future success.. Come join the team that owns the technology behind AWS People Planning products, services, and metrics. We leverage technology to improve the experience of AWS Executives, HR/Recruiting/Finance leaders, and internal AWS planning partners. A Sr. Data Scientist in the AWS Workforce Planning team, will partner with Software Engineers, Data Engineers and other Scientists, TPMs, Product Managers and Senior Management to help create world-class solutions. We're looking for people who are passionate about innovating on behalf of customers, demonstrate a high degree of product ownership, and want to have fun while they make history. You will leverage your knowledge in machine learning, advanced analytics, metrics, reporting, and analytic tooling/languages to analyze and translate the data into meaningful insights. You will have end-to-end ownership of operational and technical aspects of the insights you are building for the business, and will play an integral role in strategic decision-making. Further, you will build solutions leveraging advanced analytics that enable stakeholders to manage the business and make effective decisions, partner with internal teams to identify process and system improvement opportunities. As a tech expert, you will be an advocate for compelling user experiences and will demonstrate the value of automation and data-driven planning tools in the People Experience and Technology space. Key job responsibilities * Engineering execution - drive crisp and timely execution of milestones, consider and advise on key design and technology trade-offs with engineering teams * Priority management - manage diverse requests and dependencies from teams * Process improvements – define, implement and continuously improve delivery and operational efficiency * Stakeholder management – interface with and influence your stakeholders, balancing business needs vs. technical constraints and driving clarity in ambiguous situations * Operational Excellence – monitor metrics and program health, anticipate and clear blockers, manage escalations To be successful on this journey, you love having high standards for yourself and everyone you work with, and always look for opportunities to make our services better.
DE, BE, Berlin
Interested in solving challenging problems using latest developments in Large Language Models and Artificial Intelligence to protect the global AWS platform from fraud ? The AWS Fraud Prevention organisation is looking for a talented Applied Scientist with a solid background in the design and development of scalable AI and ML systems and services, deep passion for building ML-powered products, a proven track record of executing complex projects, and delivering high business and customer impact. You will help us develop fraud prevention strategies leveraging AI technologies and add to our expansive portfolio of ML based mitigations. As a member of our team, you'll work on projects that directly impact millions of customers, organizations , and employees every single day. This role will provide exposure to state-of-the-art innovations in AI/ML systems (including GenAI). Technologies you will have exposure to, and/or will work with, include AWS Bedrock, Amazon Q, SageMaker, and Foundational Models such as Titan, Anthropic’s Claude, Mistral, among others. You’ll be part of a team of Applied Scientists, Research Scientists, Data Scientists, Investigations Analysts, and Technical & non-Technical Program Managers and Software Engineers. As an Applied Scientist, you will work directly with these folks to monitor the flavor/ trend of exploits AWS worldwide and design appropriate solutions to respond in a collaborative environment. There are no walls, and success is based on by your ability to dive deep, and understand the subtle demands new and complex services will place upon systems and teams. As an Applied Scientist your responsibilities will include: - Develop and apply state-of-the-art Machine Learning methods to large amounts of data from different sources to build and productionalize fraud prevention, detection and mitigation solutions - Actively contribute to the development of our ML Ops infrastructure - Actively contribute to the creation and delivery of our science roadmap which includes Gen AI efforts - Work closely with software engineering teams to deploy your innovations. - Mentor and coach junior scientists - Publish your work at internal and external conferences/journals - Providing on-call product support approximately once every 3 months On Call Responsibility. This position involves on-call responsibilities to support emergent customer impacting events. Our on-call fraud escalation support occurs approximately once every 12 weeks. This Applied Scientist is also expected to play a key role in raising the AI/ML skillset within the organization, so a passion for teaching/mentoring is important. This involves bringing deep AI/ML expertise to collaborations with other scientists, leading lunch & learn session, conducting tech talks, setting up regular office hours, evangelizing lessons learned & industry best practices, and more. The ideal candidate is one who possesses notable pedigree in ML-related academic work, along with deep, real-world, hands-on experience in executing/shipping AI-based products in a fast-paced setting. You will be looked up to as an ML expert that our organization’s leadership can rely on for guidance on AI/ML topics. Mentorship & Career Growth: Our team is dedicated to supporting new members. We have a broad mix of experience levels, functions and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded professional and enable them to take on more complex tasks in the future. Learn and Be Curious: We have a formal mentor search application that lets you find a mentor that works best for you based on location, job family, job level etc. Your manager can also help you find a mentor or two, because two is better than one. In addition to formal mentors, we work and train together so that we are always learning from one another, and we celebrate and support the career progression of our team members. Inclusion and Diversity. Our team is diverse! We drive towards an inclusive culture and work environment. We are intentional about attracting, developing, and retaining amazing talent from diverse backgrounds. Team members are active in Amazon’s 10+ affinity groups, sometimes known as employee resource groups, which bring employees together across businesses and locations around the world. These range from groups such as the Black Employee Network, Latinos at Amazon, Indigenous at Amazon, Families at Amazon, LGBTQ+, Warriors at Amazon (Military), Amazon People With Disabilities, and more. Learn more about Amazon on our Day 1 Blog: https://blog.aboutamazon.com About AWS Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the preferred 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 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. About the team Utility Computing (UC) 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, including support for customers who require specialized security solutions for their cloud services.
IL, Tel Aviv
Come build the future of entertainment with us. Are you interested in helping shape the future of movies and television? Do you want to help define the next generation of how and what Amazon customers are watching? Prime Video is a premium streaming service that offers customers a vast collection of TV shows and movies - all with the ease of finding what they love to watch in one place. We offer customers thousands of popular movies and TV shows from Originals and Exclusive content to exciting live sports events. We also offer our members the opportunity to subscribe to add-on channels which they can cancel at any time and to rent or buy new release movies and TV box sets on the Prime Video Store. Prime Video is a fast-paced, growth business - available in over 240 countries and territories worldwide. The team works in a dynamic environment where innovating on behalf of our customers is at the heart of everything we do. If this sounds exciting to you, please read on We are seeking an exceptional Applied Scientist to join our Prime Video Sports tech team in Israel. Our team is dedicated to developing state-of-the-art science to allow for personalizing the customers’ experience and customers to seamlessly find any live event in our selection. You will have the opportunity to work on innovative, large-scale projects that push the boundaries of what's possible in sports content delivery and engagement. Your expertise will be crucial in tackling complex challenges such as temporal information retrieval, leveraging Generative AI and Large Language Models (LLMs), and building state-of-the-art recommender systems. Key job responsibilities We are looking for an Applied Scientist with domain expertise in Personalization, Information Retrieval, and Recommender Systems, or general ML to lead the development of new algorithms and end-to-end solutions. As part of our team of applied scientists and software development engineers, you will be responsible for researching, designing, developing, and deploying algorithms into production pipelines. Your role will involve working with cutting-edge technologies such as Gen AI/LLMs to enhance content discovery and search capabilities. You'll also tackle unique challenges like temporal information retrieval to improve real-time sports content recommendations. As a technologist, you will drive the publication of original work in top-tier conferences in Machine Learning and Information Retrieval. We expect you to thrive in ambiguous situations, demonstrating outstanding analytical abilities and comfort in collaborating with cross-functional teams and systems. The ideal candidate is a self-starter with the ability to learn and adapt quickly in our fast-paced environment. About the team We are the Prime Video Sports team. In September 2018 Prime Video launched its first full-scale live streaming experience to world-wide Prime customers with NFL Thursday Night Football. That was just the start. Now Amazon has exclusive broadcasting rights to major leagues like NFL Thursday Night Football, Tennis major like Roland-Garros and English Premium League to list few and are broadcasting live events across 30+ sports world-wide. Prime Video is expanding not just the breadth of live content that it offers, but the depth of the experience. This is a transformative opportunity, the chance to be at the vanguard of a program that will revolutionize Prime Video, and the live streaming experience of customers everywhere.