Robotics call for proposals - Spring 2026

Robotics call for proposals - Spring 2026 is sponsored by Amazon Science (Amazon Research Awards). This call for proposals from Amazon Research Awards seeks to advance robotics technology for capable, safe, and intelligent robots operating alongside people in complex real-world environments.

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Carnegie Mellon University Tennessee State University University of California, Los Angeles University of Illinois Urbana-Champaign University of Southern California University of Texas at Austin Carnegie Mellon University Tennessee State University University of California, Los Angeles University of Illinois Urbana-Champaign University of Southern California University of Texas at Austin Meet the team building useful AI agents.

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Postdoctoral Science Program Early-career research opportunities alongside experienced industry scientists. Robotics call for proposals - Spring 2026 Pursuing the future of robotics research. By Amazon Research Awards team Amazon is advancing robotics technology to enable capable, safe, and intelligent robots that can operate alongside people in complex real-world environments.

Amazon robotics designs, codes, builds, and manufactures game-changing software applications, control systems, robotics, and related hardware that is revolutionizing Amazon's operations across the globe.

We welcome proposals in the following research topics: AI for Robotics and Human-Robot Interaction : Topics of interest include multi-modal perception of complex 3D scenes and situations; multi-modal task grounding from human instructions spanning language, vision, gestures, and references to priors; and understanding long-term object dynamics in environments shared with people.

Areas of interest also include the effects of robot embodiment, and personality expression on user engagement, trust formation, and long-term acceptance in repeated interactions; legibility and transparency of autonomous robot intent, action, and decision-making in collaborative settings; and multi-modal communication strategies for robot error recovery, clarification, and repair in collaborative tasks.

Autonomous Navigation: Relevant areas include geometry-aware navigation accounting for the robot's configuration and payload; integration of multi-modal perception for navigation; reinforcement learning-based control policies for task-specific object interaction (e.g., doors and drawers); and scalable data generation for policy training.

Manipulation in Cluttered and Unstructured Environments : Topics of interest include manipulation under occlusion, stacking, and packing scenarios; compositional approaches to general-purpose manipulation; and non-prehensile manipulation related to contact force sensing and control; compliant control; generalizable surface and sweeping manipulation, impulsive manipulation, use of large multimodal models, and teleoperation.

Physical Reasoning and World Models : Relevant topics include world models learned from multimodal sensory data (vision, force, and tactile); causal reasoning about contact dynamics; semantic abstractions for contact-rich tasks; and simulation and synthetic data for real-world transfer.

Data for Manipulation : Topics of interest include physically grounded scenario and trajectory synthesis, including long-horizon task sequences; cross-embodiment transfer and retargeting; demonstration transfer across manipulation targets; synthetic data augmentation for novel object manipulation; and automated data quality evaluation methods.

Safety-Critical Control and Safe Reinforcement Learning: Relevant areas include safety for manipulation in complex environments; compliant body control and safe contact-rich control; body control robust to external disturbances; verification and monitoring of RL controller performance; safety-constrained reinforcement learning; and robust and verifiable human detection and localization.

Theoretical advances, creative new ideas, and practical applications are all welcome Submission period: March 25 — May 13, 2026 (11:59 PM Pacific Time).

Decision letters will be sent out in August 2026 Selected Principal Investigators (PIs) may receive the following: Unrestricted funds, no more than $50,000 USD on average AWS Promotional Credits, no more than $50,000 USD on average Training resources, including AWS tutorials and hands-on sessions with Amazon scientists and engineers Awards are structured as one-time unrestricted gifts.

The budget should include a list of expected costs specified in USD, and should not include administrative overhead costs. The final award amount will be determined by the awards panel. Please refer to the ARA Program rules on the rules and eligibility page .

Proposals should be prepared according to the proposal template and are encouraged to be a maximum of 3 pages, not including Appendices. Robotics will make the funding decisions based on the potential impact to the research community and the quality of the scientific content.

Expectations from recipients Amazon Research Awards team The 10 most viewed publications of 2025 From foundation model safety frameworks and formal verification at cloud scale to advanced robotics and multimodal AI reasoning, these are the most viewed publications from Amazon scientists and collaborators in 2025.

The 10 most viewed blog posts of 2025 From quantum computing breakthroughs and foundation models for robotics to the evolution of Amazon Aurora and advances in agentic AI, these are the posts that captured readers' attention in 2025.

Amazon Research Awards issues Spring 2026 call for proposals Amazon Research Awards team Submissions open March 25 and close on May 13, 2026 We are seeking an Applied Scientist to lead the development of evaluation frameworks and data collection protocols for robotic capabilities. In this role, you will focus on designing how we measure, stress-test, and improve robot behavior across a wide range of real-world tasks.

Your work will play a critical role in shaping how policies are validated and how high-quality datasets are generated to accelerate system performance. You will operate at the intersection of robotics, machine learning, and human-in-the-loop systems, building the infrastructure and methodologies that connect teleoperation, evaluation, and learning.

This includes developing evaluation policies, defining task structures, and contributing to operator-facing interfaces that enable scalable and reliable data collection. The ideal candidate is highly experimental, systems-oriented, and comfortable working across software, robotics, and data pipelines, with a strong focus on turning ambiguous capability goals into measurable and actionable evaluation systems.

Key job responsibilities - Design and implement evaluation frameworks to measure robot capabilities across structured tasks, edge cases, and real-world scenarios - Develop task definitions, success criteria, and benchmarking methodologies that enable consistent and reproducible evaluation of policies - Create and refine data collection protocols that generate high-quality, task-relevant datasets aligned with model development needs - Build and iterate on teleoperation workflows and operator interfaces to support efficient, reliable, and scalable data collection - Analyze evaluation results and collected data to identify performance gaps, failure modes, and opportunities for targeted data collection - Collaborate with engineering teams to integrate evaluation tooling, logging systems, and data pipelines into the broader robotics stack - Stay current with advances in robotics, evaluation methodologies, and human-in-the-loop learning to continuously improve internal approaches - Lead technical projects from conception through production deployment - Mentor junior scientists and engineers Applied Scientist, Prime Video - Content Localization, Understanding & Enrichment 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 subscriptions such as Apple TV+, HBO Max, Peacock, 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 team member, 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! As an Applied Scientist, you will apply state of the art natural language processing and computer vision research to video centric digital media.

We are looking for scientists with expertise in vision-language models/multimodal LLMs and long-form content understanding (full movies/episode vs. short clips). You will be dealing with architectures that handle long-context understanding and causal reasoning across extended temporal sequences. Key job responsibilities Our team builds multi-modal machine learning technologies to enrich and understand video content.

We aim not only to understand individual components within the content itself, but also their relationships to each other to provide a holistic and broader contextual understanding. This powers the next generation of video understanding and search capabilities for Prime Video.

About the team Prime Video's Content Localization, Understanding & Enrichment organization is responsible for 1) enabling Prime Video to "see" and "understand" video content including characters, scenes, dialogue, events & visual elements and 2) delivering localized, accessible content that meets a consistent cinematic quality standard at scale.

This team's mission is to deeply understand all content and empower all customers with relevant language options, innovative accessibility assists, and rich title-information across all their content-experiences on Prime Video. We create and publish content on-time that's meaningful, accurate, and accessible to every customer globally. We delight our customers by pushing the boundaries of content understanding and enrichment.

Through inclusion and innovation, we do the most fulfilling work of our career. Applied Science Manager, Center for Quantum Computing The Amazon Center for Quantum Computing (CQC) is seeking to hire an Applied Science Manager to lead a team of scientists in the physical design and simulation of superconducting quantum processors.

In this role, you will use advanced modeling, simulation, and experimental design to drive improvements in scaling and performance. You will partner with other physics and engineering teams to advance the development of fault-tolerant quantum computers.

Key job responsibilities - Hire Applied Scientists from diverse technical backgrounds to design quantum processors and improve the design process - Develop scientific talent through goal setting, feedback, collaborative work, and coaching - Collaborate with other science teams in designing experiments to overcome scaling and performance limitations - Influence engineering team development priorities in enabling systematic processor design and simulation workflows - Manage tactical and strategic initiatives with scientific projects pursued within team - Enable creative and innovative experimentation while striving for operational excellence About the team The Amazon Center for Quantum Computing (CQC) is a multi-disciplinary team of scientists, engineers, and technicians, on a mission to develop a fault-tolerant quantum computer.

Inclusive Team Culture Here at Amazon, 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.

Diverse Experiences Amazon 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.

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.

Export Control Requirement Due to applicable export control laws and regulations, candidates must be either a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum, or be able to obtain a US export license. If you are unsure if you meet these requirements, please apply and Amazon will review your application for eligibility.

Sr Data Scientist, SPX AI Lab, SPX Science Amazon Seller Assistant is our flagship GenAI-first, multi-agent system that reimagines Seller experience. Our vision is to provide each seller with a proactive, autonomous, agentic assistant that understands their business and helps them navigate the complexities of selling by anticipating their needs, surfacing insights, resolving issues, taking actions on their behalf, and helping them grow.

Amazon Seller Assistant helps millions of sellers on Amazon serve billions of customers worldwide. We are seeking a world-class Senior Data Scientist to help define and build the next generation of Amazon Seller Assistant.

You will partner with top-tier scientist, engineers and product teams to launch production-grade agentic capabilities at Amazon's scale — owning your problem space end-to-end, from a crisp customer insight to a shipped product that millions of sellers rely on. Key job responsibilities • Own the science vision, strategy, and roadmap for a key Seller Assistant capability area.

• Define and ship agentic experiences — sub-agent onboarding, tool onboarding, evaluations— that solve hard seller problems at scale. • Partner with scientists and engineers to translate frontier AI research into production-grade features sellers trust and depend on. • Design rigorous evaluation frameworks — automated and human-in-the-loop — to measure agent quality, accuracy, and business impact.

• Deep-dive into seller data, identify unmet needs, and write compelling PRFAQs that set the direction for your team. • Drive cross-functional alignment across science, engineering, UX, and business teams to deliver with speed and quality.

About the team Amazon Seller Assistant team operates at the very frontier of agentic AI and agentic commerce — not as a research group, but as a team shipping production-grade, multi-agent systems used by millions of sellers worldwide. We move with the urgency of a startup and the resources of the world's most customer-obsessed company, the latest breakthroughs in science and engineering into capabilities that sellers rely on every day.

Applied SCI III - AMZ007408 MULTIPLE POSITIONS AVAILABLE Employer: Amazon Development Center U.S., Inc. Offered Position: Applied Scientist III - AMZ007408 Job Location: New York, NY Position Responsibilities: Participate in the design, development, evaluation, deployment, and updating of formal reasoning systems for security, privacy, and data protection applications.

Drive technical and scientific innovation in security automation, data protection, and privacy-preserving technologies, with a focus on developing scalable solutions for cloud environments. Develop and/or apply formal verification techniques and automated theorem proving methods for different applications in cloud security and privacy.

Collaborate with internal and external users to understand requirements and enhance formal verification and automated reasoning capabilities. Lead research and development efforts in AI security, specifically evaluate emerging threats and opportunities, including securing Generative AI systems and designing robust safeguards.

Proactively identify and explore new opportunities for deploying and leveraging formal reasoning solutions across various domains. Applied Scientist, AWS Automated Reasoning The Agentic Automated Reasoning Group is building the next generation of software verification tools combining advances in artificial intelligence, the computational capacity of the cloud, and our deep expertise in the domain.

Join us if you want to be a part of this transformational endeavor. The Strata team (https://github. com/strata-org) is seeking an applied scientist with broad interest and expertise in model checking, interactive theorem proving, programming language semantics, and generative AI.

You will combine your expertise with that of your coworkers to build new tools that solve code analysis problems previously considered beyond reach. Our application areas span all the way from Infrastructure as Code to high-performance cryptography written in assembly code, while our methods span from interactive theorem proving to automated test generation.

Each day, hundreds of thousands of developers make billions of transactions worldwide on AWS. They harness the power of the cloud to enable innovative applications, websites, and businesses. Using automated reasoning technology and mathematical proofs, AWS allows customers to answer questions about security, availability, durability, and functional correctness.

We call this provable security, absolute assurance in security of the cloud and in the cloud. https://aws. amazon.

com/security/provable-security/ Key job responsibilities Work with customer teams to understand the nature of their software and the properties they need to establish of it. Identify tools and methods capable of addressing the verification needs of customers, including any novel analysis capabilities required.

Use techniques spanning property-based testing to model checkers, and interactive theorem provers to establish program properties. Explore generative AI techniques to help customers formalize their requirements, find revealing tests, generate required boiler plate for testing and model checking, and find and repair program proofs.

About the team The Agentic Automated Reasoning Group at AWS develops and applies state of the art formal methods and automated reasoning techniques to ensure the security, reliability, and correctness of AWS services and customer applications, with a strong focus on AI based agents. Our work innovates tools and services to perform verification at scale and apply them to build safe and secure systems at AWS.

We are also pioneering the use of formal verification and automated reasoning to develop agentic systems, ensuring AI agents operate within defined safety boundaries. Member of Technical Staff, FAR (Frontier AI & Robotics) Join the next revolution in robotics at Amazon's Frontier AI & Robotics team, where you'll work alongside world-renowned AI pioneers to lead key initiatives in robotic intelligence.

As a Member of Technical Staff, you'll spearhead the development of breakthrough foundation models that enable robots to perceive, understand, and interact with the world in unprecedented ways.

You'll drive technical excellence in areas such as perception, manipulation, science understanding, sim2real transfer, multi-modal foundation models, and multi-task learning, designing novel algorithms that bridge the gap between state-of-the-art research and real-world deployment at Amazon scale.

In this role, you'll combine hands-on technical work with scientific leadership, ensuring your team delivers robust solutions for dynamic real-world environments. You'll leverage Amazon's vast computational resources to tackle ambitious problems in areas like very large multi-modal robotic foundation models and efficient, promptable model architectures that can scale across diverse robotic applications.

Key job responsibilities - Lead technical initiatives in robotics foundation models, driving breakthrough approaches through hands-on research and development in areas like open-vocabulary panoptic scene understanding, scaling up multi-modal LLMs, sim2real/real2sim techniques, end-to-end vision-language-action models, efficient model inference, video tokenization - Design and implement novel deep learning architectures that push the boundaries of what robots can understand and accomplish - Guide technical direction for specific research initiatives, ensuring robust performance in production environments - Mentor and support fellow scientists while maintaining strong individual technical contributions - Collaborate with engineering teams to optimize and scale models for real-world applications - Influence technical decisions and implementation strategies within your area of focus A day in the life - Develop and implement novel foundation model architectures, working hands-on with our extensive compute infrastructure - Guide and support fellow scientists in solving complex technical challenges, from sim2real transfer to efficient multi-task learning - Lead focused technical initiatives from conception through deployment, ensuring successful integration with production systems - Drive technical discussions within your team and with key stakeholders - Conduct experiments and prototype new ideas using our massive compute cluster - Mentor team members while maintaining significant hands-on contribution to technical solutions Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children.

Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: 1. Medical, Dental, and Vision Coverage 2.

Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) Plan If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you!

At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply! About the team At Frontier AI & Robotics, we're not just advancing robotics – we're reimagining it from the ground up.

Our team is building the future of intelligent robotics through ground breaking foundation models and end-to-end learned systems. We tackle some of the most challenging problems in AI and robotics, from developing sophisticated perception systems to creating adaptive manipulation strategies that work in complex, real-world scenarios. What sets us apart is our unique combination of ambitious research vision and practical impact.

We leverage Amazon's massive computational infrastructure and rich real-world datasets to train and deploy state-of-the-art foundation models. Our work spans the full spectrum of robotics intelligence – from multimodal perception using images, videos, and sensor data, to sophisticated manipulation strategies that can handle diverse real-world scenarios.

We're building systems that don't just work in the lab, but scale to meet the demands of Amazon's global operations. Join us if you're excited about pushing the boundaries of what's possible in robotics, working with world-class researchers, and seeing your innovations deployed at unprecedented scale.

Applied Scientist II, Demand Enablement, Product Analytics and Operations In this role, you will design and build intelligent multi-agent systems that automate root cause analysis for advertising campaign delivery at scale.

You will architect agentic orchestration patterns where specialized sub-agents (campaign diagnostics, deal-level troubleshooting, pacing control) are invoked as composable tools by a reasoning layer that determines which subsystems to query based on the nature of the issue.

You will develop hierarchical analysis frameworks that move from daily trend detection to intra-day anomaly isolation, enabling the system to pinpoint when and why delivery degraded rather than relying on static time windows.

You will build self-learning feedback loops where the system identifies recurring failure signatures (auction dynamics, pacing anomalies, supply contention), updates its diagnostic knowledge as engineering teams deploy fixes, and retires stale patterns automatically.

We are looking for a passionate Applied Scientist with technical expertise in LLM-based agent architectures, retrieval-augmented generation, time-series anomaly detection, and production ML systems.

In addition to hands-on experience building agentic AI solutions, an ideal candidate should demonstrate the ability to translate complex distributed system behaviors into structured diagnostic reasoning, show a willingness to push the boundaries of how LLMs interact with real-time operational data, and thrive in an environment where you ship production systems that directly reduce advertiser escalation time from days to minutes.

Key job responsibilities * Conduct deep data analysis to derive insights for the business, identify gaps, and uncover new opportunities. * Develop scalable and effective machine learning models and optimization strategies to solve business problems. * Run regular A/B experiments, gather data, and perform statistical analysis to optimize advertiser experiences.

* Collaborate closely with software engineers to deliver end-to-end solutions into production. * Enhance the scalability, efficiency, and automation of large-scale data analytics, model training, deployment, and serving. * Research and implement new machine learning models and techniques to improve advertising performance.

A day in the life Your primary focus is building a multi-agent diagnostic system that automates root cause analysis for advertising campaign delivery issues. On a typical day, you might review how the system handled recent escalations, identify where it reasoned incorrectly, adjust orchestration logic, and write new evaluation cases.

You will design agent architectures that invoke specialized sub-agents as tools, build hierarchical analysis frameworks that move from trend detection to anomaly isolation, and develop self-learning loops that keep the system's diagnostic knowledge current as the underlying platform evolves.

You will work closely with SDEs building the diagnostic platform, product managers defining the troubleshooting experience, and the support teams who rely on your system to resolve advertiser delivery issues in minutes instead of days.

Beyond the core agent work, you may find yourself diving into causal inference to measure recommendation effectiveness, prototyping proactive anomaly detection, or contributing to evaluation science for systems that reason over complex operational data.

About the team The Demand Enablement, Product Analytics and Operations team builds the diagnostic and intelligence layer for Amazon DSP, the demand-side platform powering Amazon's programmatic advertising business. We own the systems that detect, diagnose, and surface delivery issues across campaigns, giving internal teams and advertisers the visibility to act before problems impact spend.

Our product portfolio spans automated troubleshooting platforms, advertiser-facing delivery insights, and AI-powered root cause analysis using multi-agent architectures on foundation models. We are a small, high-ownership team that ships production systems end-to-end, from data pipelines processing billions of bid events to LLM-based agents that reason over complex advertising systems.

If you want to work at the intersection of applied science, distributed systems observability, and real business impact measured in advertiser dollars recovered, this is the team. Sr Manager, Applied Science, AWS Compliance & Security Assurance About the Team Our team builds and operates automated reasoning technology that powers security and privacy assurance across Amazon and AWS at scale.

Our technology is deeply integrated into critical Amazon and AWS security workflows. We operate at the intersection of automated reasoning, program analysis, and applied security — and our work directly impacts the security posture of every AWS service. About the Role We are looking for an experienced Applied Science Manager to lead the team's static analysis platform science team.

In this role, you will own the technical vision and roadmap for our automated reasoning engine's static analysis capabilities, drive innovation in scalable program analysis, and lead a team of applied scientists working at the frontier of automated reasoning for security while also contributing technically as a player/coach.

You will partner closely with security, privacy, and compliance stakeholders across AWS to expand the reach and impact of provably correct code analysis.

You will also partner closely with automated reasoning experts across the company and contribute to the science of security Key job responsibilities Technical Leadership: Own the science roadmap for our automated reasoning engine, including taint analysis, compositional heap analysis, modular method summarization, and dataflow graph generation Hands-on Contribution: Personally contribute to key research and design decisions, including prototyping novel analyses and reviewing technical artifacts Team Building & Management: Hire, develop, and retain a world-class team of applied scientists; foster a culture of scientific rigor, innovation, and operational excellence Product Integration: Partner with application security and service teams to expand our platform's integration footprint and deliver new security and privacy analysis capabilities Research & Innovation: Advance the state of the art in static program analysis, including exploring formal verification of analysis correctness (e.g., using Lean, Coq, or Dafny), expanding language support beyond Java, and developing novel analysis techniques for emerging security properties Stakeholder Engagement: Collaborate with AWS AppSec, Privacy Engineering, and service teams to understand their security assurance needs and translate them into analysis capabilities Strategic Influence: Represent our team in the broader Automated Reasoning community at Amazon; contribute to automated reasoning initiatives, and academic partnerships About the team Our team builds and operates automated reasoning technology that powers security and privacy assurance across Amazon and AWS at scale.

Our automated reasoning engine is the core technology behind our managed dataflow mapping service, which automatically tracks how data flows through AWS service teams’ code and infrastructure. Our technology is deeply integrated into critical Amazon and AWS security workflows.

We operate at the intersection of automated reasoning, program analysis, and applied security — and our work directly impacts the security posture of every AWS service. Diverse Experiences Amazon Security 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 Amazon Security? At Amazon, security is central to maintaining customer trust and delivering delightful customer experiences.

Our organization is responsible for creating and maintaining a high bar for security across all of Amazon’s products and services. We offer talented security professionals the chance to accelerate their careers with opportunities to build experience in a wide variety of areas including cloud, devices, retail, entertainment, healthcare, operations, and physical stores.

Inclusive Team Culture In Amazon Security, it’s in our nature to learn and be curious. Ongoing DEI events and learning experiences inspire us to continue learning and to embrace our uniqueness. Addressing the toughest security challenges requires that we seek out and celebrate a diversity of ideas, perspectives, and voices.

Training & 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, training, 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.

Applied Scientist II, Conversational Ad Experiences The Sponsored Products and Brands (SPB) team at Amazon Ads is re-imagining the advertising landscape through generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon. com and beyond.

We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights.

We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising.

This position will be part of the Conversational Ad Experiences team within the Amazon Advertising organization. Our cross-functional team focuses on designing, developing and launching innovative ad experiences delivered to shoppers in conversational contexts. We utilize