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.
US, CA, San Francisco
If you are interested in this position, please apply on Twitch's Career site https://www.twitch.tv/jobs/en/ About Us: Twitch is the world’s biggest live streaming service, with global communities built around gaming, entertainment, music, sports, cooking, and more. It is where thousands of communities come together for whatever, every day. We’re about community, inside and out. You’ll find coworkers who are eager to team up, collaborate, and smash (or elegantly solve) problems together. We’re on a quest to empower live communities, so if this sounds good to you, see what we’re up to on LinkedIn and Twitter, and discover the projects we’re solving on our Blog. Be sure to explore our Interviewing Guide to learn how to ace our interview process. About the Role: We are looking for an Applied Scientist to solve challenging and open-ended problems in the domain of recommendations, search, ranking and information retrieval. As an Applied Scientist on Twitch's Community team, you will use ML to help viewers find streamers and communities they’ll love. You will collaborate with a team of passionate scientists and engineers to develop these models and put them into production, where they can help Twitch's creators and viewers succeed and build communities. You will report to the Applied Science Manager on the Community Discovery Team. This position is located in San Francisco, CA. You Will: - Develop and Productionize ML algorithms for recommendations, ranking and search problems that can improve discovery on Twitch. - Collaborate with our Product and Engineering teams to work backwards from customer discovery problems, to determine the ML solution (algorithm and pipeline) to have the biggest impact on our user base in the real world. - Participate in the scientific community at Twitch, Amazon, and the broader ML and risk community. Perks - Medical, Dental, Vision & Disability Insurance - 401(k) - Maternity & Parental Leave - Flexible PTO - Amazon Employee Discount
US, WA, Bellevue
We are building a world-class last mile delivery ecosystem with Amazon Flex as a cornerstone of this strategy. Amazon Flex works directly with independent contractors, to make deliveries to our customers. With Amazon Flex, delivery partners are their own boss, build their own schedule, and choose from different types of delivery opportunities (e.g. Amazon Fresh, Whole Foods Market, and Amazon Logistics). Amazon Flex is powered by a mobile app that works in sync with our advanced systems and processes, allowing delivery partners to secure delivery offers, track their delivery progress, and more. Economists at Amazon Flex partner closely with senior management, business stakeholders, scientists and engineers, and economist leadership to solve key business problems including pricing, promotions, offer optimization, recruiting, capacity planning, and beyond. Amazon Flex Economists build econometric models using our world class data systems and apply approaches from a variety of skillsets – applied macro/time series, applied micro, econometric theory, empirical IO, empirical labor, or related fields are all highly valued skillsets at Amazon. You will work in a fast moving environment to solve business problems as a member of a cross-functional team that supports all of Amazon Last Mile Delivery Tech. You will be expected to develop techniques that apply econometrics to large data sets, address quantitative problems, and contribute to the design of automated systems across the business.
US, GA, Atlanta
Machine learning (ML) has been strategic to Amazon from the early years. We are pioneers in areas such as recommendation engines, product search, eCommerce fraud detection, and large-scale optimization of fulfillment center operations. The Generative AI team helps AWS customers accelerate the use of Generative AI to solve business and operational challenges and promote innovation in their organization. As an applied scientist, you are proficient in designing and developing advanced ML models to solve diverse challenges and opportunities. You will be working with terabytes of text, images, and other types of data to solve real- world problems. You'll design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. We’re looking for talented scientists capable of applying ML algorithms and cutting-edge deep learning (DL) and reinforcement learning approaches to areas such as drug discovery, customer segmentation, fraud prevention, capacity planning, predictive maintenance, pricing optimization, call center analytics, player pose estimation, event detection, and virtual assistant among others. AWS Sales, Marketing, and Global Services (SMGS) is responsible for driving revenue, adoption, and growth from the largest and fastest growing small- and mid-market accounts to enterprise-level customers including public sector. The AWS Global Support team interacts with leading companies and believes that world-class support is critical to customer success. AWS Support also partners with a global list of customers that are building mission-critical applications on top of AWS services. Key job responsibilities The primary responsibilities of this role are to: Design, develop, and evaluate innovative ML models to solve diverse challenges and opportunities across industries Interact with customer directly to understand their business problems, and help them with defining and implementing scalable Generative AI solutions to solve them Work closely with account teams, research scientist teams, and product engineering teams to drive model implementations and new solution A day in the life N/A About the team Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.
US, WA, Bellevue
We are a part of Amazon Alexa Devices organization with the mission “delight customers through contextual and personalized proactive experiences that keep customers informed, engaged, and productive without cognitive burden”. We are developing an advanced system using Large Language Model (LLM) technologies to deliver engaging, intuitive, and adaptive content recommendations across all Amazon surfaces. We aim to facilitate seamless reasoning and customer experiences, surpassing the capabilities of previous machine learning models. We are looking for a passionate, talented, and resourceful Applied Scientist in the field of Natural Language Processing (NLP), Recommender Systems and/or Information Retrieval, to invent and build scalable solutions for a state-of-the-art context-aware speech assistant. A successful candidate will have strong machine learning background and a desire to push the envelope in one or more of the above areas. The ideal candidate would also enjoy operating in dynamic environments, be self-motivated to take on challenging problems to deliver big customer impact, shipping solutions via rapid experimentation and then iterating on user feedback and interactions. Key job responsibilities As an Applied Scientist on the team, you will collaborate with other applied scientists and engineers to develop novel algorithms to enable timely, relevant and delightful recommendations and conversations. Your work will directly impact our customers in the form of products and services that make use of various machine learning, deep learning and language model technologies. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in the state of art.
US, WA, Bellevue
The Fulfillment by Amazon (FBA) team is looking for a passionate, curious, and creative Research Scientist, with expertise and experience in operations research, operations management, supply chains, and revenue management, to join our top-notch cross-domain FBA science team. As a research scientist you will be responsible for designing and implementing cutting edge optimization models and machine learning models and building automated inventory management system to solve key challenges facing the worldwide FBA Seller business, including 1) improving FBA Seller inventory efficiency, 2) efficiently balancing the supply and demand of FBA Seller capacity, 3) closing worldwide selection gap by enabling global selling profitability, and 4) driving out costs across the FBA supply chain to spin the flywheel. Unlike many companies who buy existing off-the-shelf planning systems, we are responsible for studying, designing, and building systems to suit Amazon’s needs. Our team members have an opportunity to be on the forefront of thought leadership by working on some of the most difficult problems in the industry with some of the best product managers, research scientists/statisticians/economists and software developers in the business. This role will work with other senior and principal scientists, and partner with engineering and product teams to integrate scientific work into production systems. Key job responsibilities • Interact with engineering, operations, science and business teams to develop an understanding and domain knowledge of processes, system structures, and business requirements • Apply domain knowledge and business judgment to identify opportunities and quantify the impact aligning research direction to business requirements and make the right judgment on research project prioritization • Develop scalable mathematical models to derive optimal or near-optimal solutions to existing and new inventory planning challenges • Create prototypes and simulations to test devised solutions • Advocate technical solutions to business stakeholders, engineering teams, as well as executive level decision makers • Work closely with engineers to integrate prototypes into production systems • Create policy evaluation methods to track the actual performance of devised solutions in production systems, identify areas with potential for improvement and work with internal teams to improve the solution with new features A day in the life As a Research Scientist, you will solve real world large inventory problems by analyzing large amounts of business data, defining new metrics and business cases, designing simulations and experiments, applying supply chain modeling techniques, creating optimization models, and collaborating with teammates in business, software, and research. The successful candidate has solid research experience in Operations Research preferably with focus on Operations Management or other closely related areas or in area of Machine Learning. He or she will lead the research where we are responsible for developing solutions to better manage and optimize worldwide FBA inventory capacity, while providing the best experience to our Sellers to growth their business. About the team Fulfillment by Amazon (FBA) is a service that allows sellers to outsource order fulfillment to Amazon, allowing sellers to leverage Amazon’s world-class facilities to provide customers Prime delivery promise. Sellers gain access to Prime members worldwide, see their sales lift, and are free to focus their time and resources on what they do best while Amazon manages fulfillment. Over the last several years, sellers have enjoyed strong business growth with FBA shipping more than half of all products offered by Amazon. FBA focuses on helping sellers with automating and optimizing the third-party supply chain. FBA sellers leverage Amazon’s expertise in machine learning, optimization, data analytics, econometrics, and market design to deliver the best inventory management experience to sellers. We work full-stack, from foundational backend systems to future-forward user interfaces. Our culture is centered on rapid prototyping, rigorous experimentation, and data-driven decision-making.
US, WA, Seattle
Are you passionate about delighting hundreds of millions of customers and building the best search experience to help customers make well-informed purchase decisions on Amazon? Are you passionate about building the next generation product shopping and search experience? The Search and Discover experience on Amazon is central to every customer’s shopping mission and purchasing journey. Amazon Search is looking for a self-driven, customer obsessed, and seasoned research scientist to drive the overall search customer insights efforts and measure customer perceptions for Amazon Search. If you are passionate about using user research & customer insights to influence the future direction of Amazon Search and building a small but top notch user research science team, this is a job for you. In this highly visible role, you will work across cross-functional teams and collaborate with partners to drive user research planning, align research goals to the product roadmap, and own user research execution and final deliverables to make sure that we are always positioned to exceed customer expectations. You will present the search customer insights to various stakeholders including senior executives. Key job responsibilities * Design and conduct significantly complex research studies that impact long-term product strategy and the future of customer experience. * Build customer perception measurements for Amazon search experience and develop the methods to correlate customer perception with search experience improvements. * Define search customer insights research strategy, own the research roadmap and prioritize research opportunities across different areas. * Identify customer segments and latent customer needs, define and improve methodologies, data collection, analysis/synthesis, and identify opportunities to improve customer experience. * Manage multiple customer insights research project execution, prioritization, and ensure research projects timely delivery at the highest quality levels. * Adapt and/or create new customer insights research methodologies and workflows to support product goals at scale and work effectively with agencies and vendors. * Work cross functionally and collaborate with technical product managers, technical program managers, UX designers, science, and engineering teams to proactively plan research and align research goals to the product roadmap. * Work with data analysts/data scientists to correlate qualitative research with quantitative data analysis, and interpret complicated data across quantitive and behavioral analysis. * Own customer insights research results and prioritization communication with all stakeholders including senior executives. * Build, manage, and grow a small team of research scientists. About the team Our team operate in a friendly, fast-paced, and diverse and inclusive work environment. We are driven by the excitement of inventing products, building technologies, and providing services that change lives. We embrace new ways of doing things, make decisions quickly, and are not afraid to fail. We have the scope, benefits, and support of a large company and the spirit and heart of a small startup. At Amazon, our mission is to be Earth’s most customer-centric company. Our actions, goals, projects, programs, and inventions begin and end with the customer top of mind.
US, WA, Seattle
Amazon Advertising is one of Amazon's fastest growing and most profitable businesses. Amazon's advertising portfolio helps merchants, retail vendors, and brand owners succeed via native advertising, which grows incremental sales of their products sold through Amazon. The primary goals are to help shoppers discover new products they love, be the most efficient way for advertisers to meet their business objectives, and build a sustainable business that continuously innovates on behalf of customers. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day! The Creative X org within Amazon Advertising aims to democratize access to high-quality creative assets, including copy, images and video, by building and productizing generative AI-driven tools for advertisers. We are investing in latent-diffusion and DiT models, LLMs, computer vision, reinforcement learning, and image + video synthesis. The solutions we develop will be deployed for use by self-service advertisers and agencies, as well as available to premium brands that advertise on Amazon. We are seeking an experienced science leader who is adept at a variety of skills; especially in generative AI, computer vision, and large language models that will accelerate our plans to generate high-quality creatives on behalf of advertisers. The right candidate will be an inventor at heart, provide science leadership, establish the right direction and vision, build team mechanisms, foster the spirit of collaboration and innovation within the org, and execute against a roadmap. The leader will provide both technical direction as well as manage a sizable team of scientists. They will need to be adept at recruiting, launching AI models into production, writing vision/direction documents, and building team mechanisms that will foster innovation and execution. Key job responsibilities * Drive end-to-end applied science projects that have a high degree of ambiguity, scale, complexity * Provide technical / science leadership related to computer vision, large language models, and generative image + video. * Research new and innovative machine learning approaches. * Recruit high performing Applied Scientists to the team and provide mentorship. * Establish team mechanisms, including team building, planning, and document reviews.
CA, BC, Vancouver
Technology is giving the beauty industry a makeover! Are you interested to disrupt and redefine the way customers buy Beauty products online? Are you interested in using the latest advances in machine learning, computer vision, and big-data technologies to build online customer experiences for Beauty products that can equal or even surpass an in-store experience? Amazon Beauty is reinventing the shopping experience for all beauty customers across the largest selection of brands to become the most trusted beauty destination. Beauty is unique in retail with a diverse customer set along with products that are emotional, fun, and creative. This is your chance to get in on the ground floor to build something entirely new and transform an industry! To achieve our vision, we think big and tackle technological challenges every day. We need builders and disruptors who are not afraid to innovate! Our architecture and development processes support rapid experimentation, global deployments, and self-service capabilities that allow us to scale better. We build: - Amazon scale systems: All our technology needs to work at Amazon scale, serving millions of customers with millisecond-level latency. - Immersive customer experiences: We will create elevated and immersive customer experiences that using cutting-edge UI-technologies and user-centric design patterns. - Computer Vision and augmented reality (AR) experiences: We bring exciting experiences directly to the customer's mobile phone using their cameras and combinations of computer vision and AR. - Personalization using machine learning: We use latest advances in ML and GenAI to provide better-personalized shopping experiences. - Data & analytics pipelines: Amazon is data-driven, and a robust data backbone is necessary for our systems. We build on core AWS services such as EC2, S3, DynamoDB, SageMaker, StepFunctions, etc. - Multi-device support: We build for all traditional surfaces - desktop browsers, mobile browsers, and mobile applications. Key job responsibilities We are looking for talented and innovation-driven scientists who are passionate about leveraging the latest advances in Generative AI, Diffusion Models, Computer Vision (CV), Graphics, AR/VR, Virtual Try-On, Image Processing, and related technologies, to solve customer problems in the Beauty space. You will have an opportunity to revolutionize the customer shopping experience across the world's most extensive catalog of beauty products. You will be directly responsible for leading the ideation, design, prototyping, development, and launch of innovative scientific solutions that address customer problem in the beauty and shopping space. You will closely partner with product managers, UX designers, engineers, and the broader Amazon scientific community to pioneer state-of-the-art solutions to extremely challenging problems in machine learning and CV. You will be our organization's Tech Evangelist and represent our organization in key internal and external AI, ML, or Vision conferences. About the team Amazon Beauty Tech is a key and essential part of the Consumables organization and North America Stores. We are a passionate group of engineers, scientists, product managers, and designers who drive technological innovation to improve the customer shopping experience. We have a startup-like work culture where innovation is encouraged; we are never afraid to propose big ideas for fear of failing!
US, CA, Sunnyvale
The Artificial General Intelligence (AGI) team is looking for a highly skilled and experienced Senior Applied Scientist, to lead the development and implementation of cutting-edge algorithms and models for supervised fine-tuning and reinforcement learning through human feedback; with a focus across text, image, and video modalities. As a Senior Applied Scientist, you will play a critical role in driving the development of Generative Artificial Intelligence (GenAI) technologies that can handle Amazon-scale use cases and have a significant impact on our customers' experiences. Key job responsibilities - Collaborate with cross-functional teams of engineers, product managers, and scientists to identify and solve complex problems in GenAI - Design and execute experiments to evaluate the performance of different algorithms and models, and iterate quickly to improve results - Think big about the arc of development of GenAI over a multi-year horizon, and identify new opportunities to apply these technologies to solve real-world problems - Communicate results and insights to both technical and non-technical audiences, including through presentations and written reports - Mentor and guide junior scientists and engineers, and contribute to the overall growth and development of the team
US, CA, Santa Clara
Amazon AI is looking for world class scientists to join its Amazon Q Builder CodeGen team. Amazon Q Builder CodeGen is an LLM-based AWS service that makes developers more productive by providing them code recommendations. Amazon Q Builder CodeGen leverages large language models, program analysis, responsible AI, robustness, efficient inference techniques and a lot more in building this technology. You will invent, implement, and deploy state of the art algorithms and systems, and be at the heart of a growing and exciting focus area for AWS. Candidate experiences of interest include but are not limited to: LLM, RAG, model training and inference, trustworthy AI, responsible AI, program analysis and program synthesis in general. The Amazon Web Services (AWS) Next Gen DevX (NGDE) team uses generative AI and foundation models to reimagine the experience of all builders on AWS. From the IDE to web-based tools and services, AI will help engineers work on large and small applications. We explore new technologies and find creative solutions. Curiosity and an explorative mindset can find a place here to impact the life of engineers around the world. If you are excited about this space and want to enlighten your peers with new capabilities, this is the team for you. About the team 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. Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Hybrid Work We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our U.S. Amazon offices.