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Trusted AI Symposium 2026
January 21, 2026
New York, New York
Conference
Trusted AI Symposium 2026

Overview

Join leading researchers from academia and industry for an intensive, one-day symposium on the frontier of Trusted AI. Hosted by the Amazon AGI team behind the Nova models, this invitation-only gathering brings together distinguished scholars to address a central challenge: building powerful AI systems that are inherently safe and reliable.

Key dates

Abstract submission deadline: December 19, 2025

Notification of acceptance: January 7, 2026.

RSVP deadline: Due to high demand, invitations are issued selectively, and only confirmed attendees will receive detailed event logistics via email by January 16, 2026.

Event date: January 21, 2026

Call for posters: Closed

Deadline is December 19, 2025 and must be submitted here.

All submission is non-archival. Double submission is acceptable

What to submit
  • Format your submission following this NeurIPS 2025 LaTex template; submit as PDF.
  • Extended abstract (1-2 pages) describing your research, methodology, and key findings
  • Abstracts should follow a standard academic format (introduction, methods, results, conclusions)
  • Include author names, affiliations, and email
  • Indicate if the work uses or evaluates Amazon Nova models
Papers that discuss, evaluate, or utilize Amazon Nova models will receive priority in the selection process. To support this, Amazon is offering a limited free access tier for Nova models in the North American region, available directly at https://nova.amazon.com/dev/api.

Topics of interest
We welcome submissions across all aspects of Trusted AI, including but not limited to:
  • AI governance & policy: Frameworks, compliance, and regulatory approaches
  • Evaluation & benchmarking in RAI: Metrics, testing methodologies, and assessment frameworks
  • Risk mitigation: Techniques for reducing AI harms and unintended behaviors
  • Security & safety: Adversarial robustness, secure deployment, and threat modeling
  • Agent safety & reliability: Safety in agentic, autonomous, and multi-agent systems
  • Explainability & interpretability: Making AI decisions transparent and understandable
  • Reasoning & verification: Formal methods and logical reasoning in AI systems
  • Observability & monitoring: Runtime monitoring and system transparency
  • Red-teaming & stress testing: Adversarial testing and failure mode discovery
  • Uncertainty quantification: Calibration, confidence estimation, and risk assessment
  • Multi-modal safety: Trust across vision, language, and other modalities
  • Multi-lingual considerations: Safety and fairness across languages and cultures
  • Content moderation: Detection and filtering of harmful content
  • Watermarking & provenance: Digital fingerprinting and attribution
  • Deception: Detection of deceptive behaviors by models

Keynote speakers

Aaron Roth, Amazon Scholar and Professor at University of Pennsylvania

Elias Bareinboim, Director of Causal AI Lab, Columbia University

Participant benefits

Selected presenters will receive:

Networking opportunities: Connect with Amazon scientists and leading academics
Research collaboration: Potential pathways to ongoing partnerships with Amazon
Job opportunities: Engage with Amazon recruiters and hiring managers
Visibility: Showcase your work to key decision-makers in Trusted AI
Amazon Nova credits: Complimentary credits to explore and experiment with Nova models

Contact us

You can reach us at trusted-ai-symposium@amazon.com.

Work with us

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Robotics - Applied Scientist II Intern / Co-op - 2026 (Robotics, Perception, Manipulation, Locomotion, Planning, HRI and more), Amazon Development Center Taiwan
TW, TPE, Hsinchu City
Are you passionate about robotics and research? Do you want to solve real customer problems through innovative technology? Do you enjoy working on scalable research and projects in a collaborative team environment? Do you want to see your science solutions directly impact millions of customers worldwide? At Amazon, we hire the best minds in technology to innovate and build on behalf of our customers. Customer obsession is part of our company DNA, which has made us one of the world's most beloved brands. We’re looking for current PhD or Master students with a passion for robotic research and applications to join us as Robotics Applied Scientist II Intern/Co-ops in 2026 to shape the future of robotics and automation at an unprecedented scale across. For these positions, our Robotics teams at Amazon are looking for students with a specialization in one or more of the research areas in robotics such as: robotics, robotics manipulation (e.g., robot arm, grasping, dexterous manipulation, end of arm tools/end effector), autonomous mobile robots, mobile manipulation, movement, autonomous navigation, locomotion, motion/path planning, controls, perception, sensing, robot learning, artificial intelligence, machine learning, computer vision, large language models, human-robot interaction, robotics simulation, optimization, and more! We're looking for curious minds who think big and want to define tomorrow's technology. At Amazon, you'll grow into the high-impact engineer you know you can be, supported by a culture of learning and mentorship. Every day brings exciting new challenges and opportunities for personal growth. By applying to this role, you will be considered for Robotics Applied Scientist II Intern/Co-op (2026) opportunities across various Robotics teams at Amazon with different robotics research focus, with internship positions available for multiple locations, durations (3 to 6+ months), and year-round start dates (winter, spring, summer, fall). Amazon intern and co-op roles follow the same internship structure. "Intern/Internship" wording refers to both interns and co-ops. Amazon internships across all seasons are full-time positions during vacation, and interns should expect to work in office, Monday-Friday, up to 40 hours per week typically between 9am-6pm. Specific team norms around working hours will be communicated by your manager. Interns should not have other employment during the Amazon work-day. Applicants should have a minimum of one quarter/semester/trimester remaining in their studies after their internship concludes. The robotics internship join dates, length, location, and prospective team will be finalized at the time of any applicable job offers. In your application, you will be able to provide your preference of research interests, start dates, internship duration, and location. While your preference will be taken into consideration, we cannot guarantee that we can meet your selection based on several factors including but not limited to the internship availability and business needs of this role.
Applied Scientist, Amazon Special Projects
US, WA, Seattle
Innovators wanted! Are you an entrepreneur? A builder? A dreamer? This role is part of an Amazon Special Projects team that takes the company’s Think Big leadership principle to the limits. If you’re interested in innovating at scale to address big challenges in the world, this is the team for you. As an Applied Scientist on our team, you will focus on building state-of-the-art ML models for biology. Our team rewards curiosity while maintaining a laser-focus in bringing products to market. Competitive candidates are responsive, flexible, and able to succeed within an open, collaborative, entrepreneurial, startup-like environment. At the forefront of both academic and applied research in this product area, you have the opportunity to work together with a diverse and talented team of scientists, engineers, and product managers and collaborate with other teams. Key job responsibilities As an Applied Science, you will have access to large datasets with billions of images and video to build large-scale machine learning systems. Additionally, you will analyze and model terabytes of text, images, and other types of data to solve real-world problems and translate business and functional requirements into quick prototypes or proofs of concept. We are looking for smart scientists capable of using a variety of domain expertise combined with machine learning and statistical techniques to invent, design, evangelize, and implement state-of-the-art solutions for never-before-solved problems. About the team Our team highly values work-life balance, mentorship and career growth. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We care about your career growth and strive to assign projects and offer training that will challenge you to become your best.
Navigation Science Manager, Prime Air
US, WA, Seattle
Here at Amazon, we embrace our differences. We are committed to furthering our culture of diversity and inclusion of our teams within the organization. How do you get items to customers quickly, cost-effectively, and—most importantly—safely, in less than an hour? And how do you do it in a way that can scale? Our teams of hundreds of scientists, engineers, aerospace professionals, and futurists have been working hard to do just that! We are delivering to customers, and are excited for what’s to come. Check out more information about Prime Air on the About Amazon blog (https://www.aboutamazon.com/news/transportation/amazon-prime-air-delivery-drone-reveal-photos). If you are seeking an iterative environment where you can drive innovation, apply state-of-the-art technologies to solve real world delivery challenges, and provide benefits to customers, Prime Air is the place for you. Come work on the Amazon Prime Air Team! Prime Air is seeking an experienced Applied Science Manager to help develop our advanced Navigation algorithms and flight software applications. In this role, you will lead a team of scientists and engineers to conduct analyses, support cross-functional decision-making, define system architectures and requirements, contribute to the development of flight algorithms, and actively identify innovative technological opportunities that will drive significant enhancements to meet our customers' evolving demands. This person must be comfortable working with a team of top-notch software developers and collaborating with our science teams. We’re looking for someone who innovates, and loves solving hard problems. You will work hard, have fun, and make history! Export Control License: This position may require a deemed export control license for compliance with applicable laws and regulations. Placement is contingent on Amazon’s ability to apply for and obtain an export control license on your behalf.
Senior Data Scientist - Data and Machine Learning, WWPS ProServe
US, VA, Herndon
Application deadline: Applications will be accepted on an ongoing basis Are you excited to help the US Intelligence Community design, build, and implement AI algorithms, including advanced Generative AI solutions, to augment decision making while meeting the highest standards for reliability, transparency, and scalability? The Amazon Web Services (AWS) US Federal Professional Services team works directly with US Intelligence Community agencies and other public sector entities to achieve their mission goals through the adoption of Machine Learning (ML) and Generative AI methods. We build models for text, image, video, audio, and multi-modal use cases, leveraging both traditional ML approaches and state-of-the-art generative models including Large Language Models (LLMs), text-to-image generation, and other advanced AI capabilities to fit the mission. Our team collaborates across the entire AWS organization to bring access to product and service teams, to get the right solution delivered and drive feature innovation based on customer needs. At AWS, we're hiring experienced data scientists with a background in both traditional and generative AI who can help our customers understand the opportunities their data presents, and build solutions that earn the customer trust needed for deployment to production systems. In this role, you will work closely with customers to deeply understand their data challenges and requirements, and design tailored solutions that best fit their use cases. You should have broad experience building models using all kinds of data sources, and building data-intensive applications at scale. You should possess excellent business acumen and communication skills to collaborate effectively with stakeholders, develop key business questions, and translate requirements into actionable solutions. You will provide guidance and support to other engineers, sharing industry best practices and driving innovation in the field of data science and AI. This position requires that the candidate selected must currently possess and maintain an active TS/SCI Security Clearance with Polygraph. The position further requires the candidate to opt into a commensurate clearance for each government agency for which they perform AWS work. Key job responsibilities As an Data Scientist, you will: - Collaborate with AI/ML scientists and architects to research, design, develop, and evaluate AI algorithms to address real-world challenges - Interact with customers directly to understand the business problem, help and aid them in implementation of AI solutions, deliver briefing and deep dive sessions to customers and guide customer on adoption patterns and paths to production. - Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholder - Provide customer and market feedback to Product and Engineering teams to help define product direction - This position may require up to 25% local travel. About the team About AWS 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 and 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.
Applied Scientist II, Machine Learning Accelerator - Annapurna Labs
US, TX, Austin
Our team is involved with pre-silicon design verification for custom IP. A critical requirement of the verification flow is the requirement of legal and realistic stimulus of a custom Machine Learning Accelerator Chip. Content creation is built using formal methods that model legal behavior of the design and then solving the problem to create the specific assembly tests. The entire frame work for creating these custom tests is developed using a SMT solver and custom software code to guide the solution space into templated scenarios. This highly visible and innovative role requires the design of this solving framework and collaborating with design verification engineers, hardware architects and designers to ensure that interesting content can be created for the projects needs. Key job responsibilities Develop an understanding for a custom machine learning instruction set architecture. Model correctness of instruction streams using first order logic. Create custom API's to allow control over scheduling and randomness. Deploy algorithms to ensure concurrent code is safely constructed. Create coverage metrics to ensure solution space coverage. Use novel methods like machine learning to automate content creation. 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 customers who require specialized security solutions for their cloud services. Annapurna Labs (our organization within AWS UC) designs silicon and software that accelerates innovation. Customers choose us to create cloud solutions that solve challenges that were unimaginable a short time ago—even yesterday. Our custom chips, accelerators, and software stacks enable us to take on technical challenges that have never been seen before, and deliver results that help our customers change the world. About 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. 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. 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. 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.
Applied Scientist Intern, International Technology, 2026 Beijing
CN, 11, Beijing
职位：Applied scientist 应用科学家实习生 毕业时间：2026年10月 - 2027年7月之间毕业的应届毕业生 · 入职日期：2026年6月及之前 · 实习时间：保证一周实习4-5天全职实习，至少持续3个月 · 工作地点：北京朝阳区 投递须知： 1 填写简历申请时，请把必填和非必填项都填写完整。提交简历之后就无法修改了哦！ 2 学校的英文全称请准确填写。中英文对应表请查这里（无法浏览请登录后浏览）https://docs.qq.com/sheet/DVmdaa1BCV0RBbnlR?tab=BB08J2 如果您正在攻读计算机，AI，ML或搜索领域专业的博士或硕士研究生，而且对应用科学家的实习工作感兴趣。如果您也喜爱深入研究棘手的技术问题并提出解决方案，用成功的产品显著地改善人们的生活。 那么，我们诚挚邀请您加入亚马逊的International Technology搜索团队改善Amazon的产品搜索服务。我们的目标是帮助亚马逊的客户找到他们所需的产品，并发现他们感兴趣的新产品。 这会是一份收获满满的工作。您每天的工作都与全球数百万亚马逊客户的体验紧密相关。您将提出和探索创新，基于TB级别的产品和流量数据设计机器学习模型。您将集成这些模型到搜索引擎中为客户提供服务，通过数据，建模和客户反馈来完成闭环。您对模型的选择需要能够平衡业务指标和响应时间的需求。
Applied Scientist Intern, 2026 Shenzhen
CN, 44, Shenzhen
职位：Applied scientist 应用科学家实习生 毕业时间：2026年10月 - 2027年7月之间毕业的应届毕业生 · 入职日期：2026年6月及之前 · 实习时间：保证一周实习4-5天全职实习，至少持续3个月 · 工作地点：深圳福田区 投递须知： 1 填写简历申请时，请把必填和非必填项都填写完整。提交简历之后就无法修改了哦！ 2 学校的英文全称请准确填写。中英文对应表请查这里（无法浏览请登录后浏览）https://docs.qq.com/sheet/DVmdaa1BCV0RBbnlR?tab=BB08J2 如果您正在攻读计算机，AI，ML领域专业的博士或硕士研究生，而且对应用科学家的实习工作感兴趣。如果您也喜爱深入研究棘手的技术问题并提出解决方案，用成功的产品显著地改善人们的生活。 那么，我们诚挚邀请您加入亚马逊。这会是一份收获满满的工作。您每天的工作都与全球数百万亚马逊客户的体验紧密相关。您将提出和探索创新，基于TB级别的产品和流量数据设计机器学习模型。您将集成这些为客户提供服务，通过数据，建模和客户反馈来完成闭环。您对模型的选择需要能够平衡业务指标和响应时间的需求。
Applied Scientist - AI/ML , Decision Intelligence team
LU, Luxembourg
Join our team as an Applied Scientist II where you'll develop innovative machine learning solutions that directly impact millions of customers. You'll work on ambiguous problems where neither the problem nor solution is well-defined, inventing novel scientific approaches to address customer needs at the project level. This role combines deep scientific expertise with hands-on implementation to deliver production-ready solutions that drive measurable business outcomes. Key job responsibilities Invent: - Design and develop novel machine learning models and algorithms to solve ambiguous customer problems where textbook solutions don't exist - Extend state-of-the-art scientific techniques and invent new approaches driven by customer needs at the project level - Produce internal research reports with the rigor of top-tier publications, documenting scientific findings and methodologies - Stay current with academic literature and research trends, applying latest techniques when appropriate Implement: - Write production-quality code that meets or exceeds SDE I standards, ensuring solutions are testable, maintainable, and scalable - Deploy components directly into production systems supporting large-scale applications and services - Optimize algorithm and model performance through rigorous testing and iterative improvements - Document design decisions and implementation details to enable reproducibility and knowledge transfer - Contribute to operational excellence by analyzing performance gaps and proposing solutions Influence: - Collaborate with cross-functional teams to translate business goals into scientific problems and metrics - Mentor junior scientists and help new teammates understand customer needs and technical solutions - Present findings and recommendations to both technical and non-technical stakeholders - Contribute to team roadmaps, priorities, and strategic planning discussions - Participate in hiring and interviewing to build world-class science teams
Applied Scientist, Artificial General Intelligence
US, CA, Sunnyvale
The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and inventive Applied Scientist with a strong deep learning background, to build Generative Artificial Intelligence (GenAI) technology with Large Language Models (LLMs) and multimodal systems. Key job responsibilities As an Applied Scientist with the AGI team, you will work with talented peers to support the development of GenAI algorithms and modeling techniques, to advance the state of the art with LLMs. Your work will directly impact our customers in the form of products and services that make use of speech and language technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in GenAI. About the team The AGI team has a mission to push the envelope with GenAI in LLMs and multimodal systems, in order to provide the best-possible experience for our customers.
Applied Science Manager, Amazon Shipping
IN, HR, Gurugram
Lead ML teams building large-scale forecasting and optimization systems that power Amazon’s global transportation network and directly impact customer experience and cost. As an Applied Science Manager, you will set scientific direction, mentor applied scientists, and partner with engineering and product leaders to deliver production-grade ML solutions at massive scale. Key job responsibilities 1. Lead and grow a high-performing team of Applied Scientists, providing technical guidance, mentorship, and career development. 2. Define and own the scientific vision and roadmap for ML solutions powering large-scale transportation planning and execution. 3. Guide model and system design across a range of techniques, including tree-based models, deep learning (LSTMs, transformers), LLMs, and reinforcement learning. 4. Ensure models are production-ready, scalable, and robust through close partnership with stakeholders. Partner with Product, Operations, and Engineering leaders to enable proactive decision-making and corrective actions. 5. Own end-to-end business metrics, directly influencing customer experience, cost optimization, and network reliability. 6. Help contribute to the broader ML community through publications, conference submissions, and internal knowledge sharing. A day in the life Your day includes reviewing model performance and business metrics, guiding technical design and experimentation, mentoring scientists, and driving roadmap execution. You’ll balance near-term delivery with long-term innovation while ensuring solutions are robust, interpretable, and scalable. Ultimately, your work helps improve delivery reliability, reduce costs, and enhance the customer experience at massive scale.
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