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AWS AI: Human-in-the-loop machine learning and annotation call for proposals — Spring 2022

Sharing learnings and ML capabilities as fully managed services, and putting them into the hands of every scientist and developer.

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About this CFP

AWS offers a broad and deep set of tools for businesses to create impactful machine learning solutions faster. Our mission is to share our learnings and ML capabilities as fully managed services, and put them into the hands of every scientist and developer. AWS AI aims to advance machine learning research by funding development of open-source tools and research that benefit the machine learning community at large, or impactful research that uses machine learning tools on AWS, including AWS AI Services, AWS ML Services (Amazon SageMaker, Amazon SageMaker Ground Truth, Amazon SageMaker Neo, and Amazon Augmented AI), and Apache MXNet on AWS.

AWS AI is soliciting funding proposals related to Human-in-the-Loop Machine Learning and Annotation. We specifically aim to solicit funding proposals that focus on innovation related to supporting annotators with machine learning and artificial intelligence. Proposals should be attached to one (or more) of the following themes:

  1. Tools and Techniques for Instructional Clarity and Accelerated Onboarding in Annotation Tasks.
  2. Interactive Tools and Techniques for Real-Time AI-Assisted Annotation.
  3. ML models for auto-labeling in low data regime that work across tasks and modalities, e.g. vision and language.
  4. 3D deep learning for autonomous driving for auto-labeling and data selection.

Timeline

  • Submission period: June 3 — July 15, 2022
  • Decision letters will be sent out December 2022

Award details

Selected Principal Investigators (PIs) may receive the following:

  • Unrestricted funds, no more than $50,000 USD on average
  • AWS Promotional Credits, no more than $40,000 USD on average
  • Training resources, including AWS tutorials and hands-on sessions with Amazon scientists and engineers

Awards are structured as one-year 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.

Eligibility requirements

Please refer to the ARA Program rules on the FAQ page.

Proposal requirements

PIs are encouraged to exemplify how their proposed techniques or research studies will apply to tasks related to human-in-the-loop machine learning and data annotation. PIs should either include plans for open source contributions or state that they do not plan to make any open source contributions (data or code) under the proposed effort. Proposals for this CFP should be prepared according to the proposal template and are encouraged to be a maximum of 4 pages, not including Appendices.

Selection criteria

ARA will make the funding decisions based on the creativity and quality of the scientific content, and potential impact to the research community and society at large.

Expectations from recipients

To the extent deemed reasonable, Award recipients should acknowledge the support from ARA. Award recipients will inform ARA of publications, presentations, code and data releases, blogs/social media posts, and other speaking engagements referencing the results of the supported research or the Award. Award recipients are expected to provide updates and feedback to ARA via surveys or reports on the status of their research. Award recipients will have an opportunity to work with ARA on an informational statement about the awarded project that may be used to generate visibility for their institutions and ARA.

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Data Scientist, Seller Fulfillment Services (SFS)
IN, KA, Bengaluru
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IN, KA, Bengaluru
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US, WA, Seattle
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Senior Manager Applied Science, Prime Video Personalization & Discovery
US, WA, Seattle
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US, CA, Santa Clara
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Applied Scientist II, AWS Just-Walk-Out Science Team
US, CA, East Palo Alto
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Applied Scientist, Console Science
US, CA, Santa Clara
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Member of Technical Staff, Frontier AI & Robotics (FAR)
US, CA, San Francisco
Join the next revolution in robotics at Amazon's Frontier AI & Robotics team, where you'll work alongside world-renowned AI pioneers to push the boundaries of what's possible in robotic intelligence. As a Member of Technical Staff, you'll be at the forefront of developing breakthrough foundation models that enable robots to perceive, understand, and interact with the world in unprecedented ways. You'll drive independent research initiatives in areas such as perception, manipulation, science understanding, locomotion, manipulation, sim2real transfer, multi-modal foundation models and multi-task robot learning, designing novel frameworks that bridge the gap between state-of-the-art research and real-world deployment at Amazon scale. In this role, you'll balance innovative technical exploration with practical implementation, collaborating with platform teams to ensure your models and algorithms perform robustly in dynamic real-world environments. You'll have access to Amazon's vast computational resources, enabling you 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 - Drive independent research initiatives across the robotics stack, including robotics foundation models, focusing on breakthrough approaches in perception, and manipulation, for example 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 - Lead full-stack robotics projects from conceptualization through deployment, taking a system-level approach that integrates hardware considerations with algorithmic development, ensuring robust performance in production environments - Collaborate with platform and hardware teams to ensure seamless integration across the entire robotics stack, optimizing and scaling models for real-world applications - Contribute to the team's technical strategy and help shape our approach to next-generation robotics challenges A day in the life - Design and implement novel foundation model architectures and innovative systems and algorithms, leveraging our extensive infrastructure to prototype and evaluate at scale - Collaborate with our world-class research team to solve complex technical challenges - Lead technical initiatives from conception to deployment, working closely with robotics engineers to integrate your solutions into production systems - Participate in technical discussions and brainstorming sessions with team leaders and fellow scientists - Leverage our massive compute cluster and extensive robotics infrastructure to rapidly prototype and validate new ideas - Transform theoretical insights into practical solutions that can handle the complexities of real-world robotics applications 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 innovative 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.
Member of Technical Staff, Frontier AI & Robotics (FAR)
US, CA, San Francisco
Join the next revolution in robotics at Amazon's Frontier AI & Robotics team, where you'll work alongside world-renowned AI pioneers to push the boundaries of what's possible in robotic intelligence. As a Member of Technical Staff, you'll be at the forefront of developing breakthrough foundation models that enable robots to perceive, understand, and interact with the world in unprecedented ways. You'll drive independent research initiatives in areas such as perception, manipulation, science understanding, locomotion, manipulation, sim2real transfer, multi-modal foundation models and multi-task robot learning, designing novel frameworks that bridge the gap between state-of-the-art research and real-world deployment at Amazon scale. In this role, you'll balance innovative technical exploration with practical implementation, collaborating with platform teams to ensure your models and algorithms perform robustly in dynamic real-world environments. You'll have access to Amazon's vast computational resources, enabling you 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 - Drive independent research initiatives across the robotics stack, including robotics foundation models, focusing on breakthrough approaches in perception, and manipulation, for example 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 - Lead full-stack robotics projects from conceptualization through deployment, taking a system-level approach that integrates hardware considerations with algorithmic development, ensuring robust performance in production environments - Collaborate with platform and hardware teams to ensure seamless integration across the entire robotics stack, optimizing and scaling models for real-world applications - Contribute to the team's technical strategy and help shape our approach to next-generation robotics challenges A day in the life - Design and implement novel foundation model architectures and innovative systems and algorithms, leveraging our extensive infrastructure to prototype and evaluate at scale - Collaborate with our world-class research team to solve complex technical challenges - Lead technical initiatives from conception to deployment, working closely with robotics engineers to integrate your solutions into production systems - Participate in technical discussions and brainstorming sessions with team leaders and fellow scientists - Leverage our massive compute cluster and extensive robotics infrastructure to rapidly prototype and validate new ideas - Transform theoretical insights into practical solutions that can handle the complexities of real-world robotics applications 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 innovative 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.
Member of Technical Staff, Frontier AI & Robotics (FAR)
US, CA, San Francisco
Join the next revolution in robotics at Amazon's Frontier AI & Robotics team, where you'll work alongside world-renowned AI pioneers to push the boundaries of what's possible in robotic intelligence. As a Member of Technical Staff, you'll be at the forefront of developing breakthrough foundation models that enable robots to perceive, understand, and interact with the world in unprecedented ways. You'll drive independent research initiatives in areas such as perception, manipulation, science understanding, locomotion, manipulation, sim2real transfer, multi-modal foundation models and multi-task robot learning, designing novel frameworks that bridge the gap between state-of-the-art research and real-world deployment at Amazon scale. In this role, you'll balance innovative technical exploration with practical implementation, collaborating with platform teams to ensure your models and algorithms perform robustly in dynamic real-world environments. You'll have access to Amazon's vast computational resources, enabling you 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 - Drive independent research initiatives across the robotics stack, including robotics foundation models, focusing on breakthrough approaches in perception, and manipulation, for example 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 - Lead full-stack robotics projects from conceptualization through deployment, taking a system-level approach that integrates hardware considerations with algorithmic development, ensuring robust performance in production environments - Collaborate with platform and hardware teams to ensure seamless integration across the entire robotics stack, optimizing and scaling models for real-world applications - Contribute to the team's technical strategy and help shape our approach to next-generation robotics challenges A day in the life - Design and implement novel foundation model architectures and innovative systems and algorithms, leveraging our extensive infrastructure to prototype and evaluate at scale - Collaborate with our world-class research team to solve complex technical challenges - Lead technical initiatives from conception to deployment, working closely with robotics engineers to integrate your solutions into production systems - Participate in technical discussions and brainstorming sessions with team leaders and fellow scientists - Leverage our massive compute cluster and extensive robotics infrastructure to rapidly prototype and validate new ideas - Transform theoretical insights into practical solutions that can handle the complexities of real-world robotics applications 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 innovative 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.
Member of Technical Staff, Frontier AI & Robotics (FAR)
US, CA, San Francisco
Join the next revolution in robotics at Amazon's Frontier AI & Robotics team, where you'll work alongside world-renowned AI pioneers to push the boundaries of what's possible in robotic intelligence. As a Member of Technical Staff, you'll be at the forefront of developing breakthrough foundation models that enable robots to perceive, understand, and interact with the world in unprecedented ways. You'll drive independent research initiatives in areas such as perception, manipulation, science understanding, locomotion, manipulation, sim2real transfer, multi-modal foundation models and multi-task robot learning, designing novel frameworks that bridge the gap between state-of-the-art research and real-world deployment at Amazon scale. In this role, you'll balance innovative technical exploration with practical implementation, collaborating with platform teams to ensure your models and algorithms perform robustly in dynamic real-world environments. You'll have access to Amazon's vast computational resources, enabling you 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 - Drive independent research initiatives across the robotics stack, including robotics foundation models, focusing on breakthrough approaches in perception, and manipulation, for example 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 - Lead full-stack robotics projects from conceptualization through deployment, taking a system-level approach that integrates hardware considerations with algorithmic development, ensuring robust performance in production environments - Collaborate with platform and hardware teams to ensure seamless integration across the entire robotics stack, optimizing and scaling models for real-world applications - Contribute to the team's technical strategy and help shape our approach to next-generation robotics challenges A day in the life - Design and implement novel foundation model architectures and innovative systems and algorithms, leveraging our extensive infrastructure to prototype and evaluate at scale - Collaborate with our world-class research team to solve complex technical challenges - Lead technical initiatives from conception to deployment, working closely with robotics engineers to integrate your solutions into production systems - Participate in technical discussions and brainstorming sessions with team leaders and fellow scientists - Leverage our massive compute cluster and extensive robotics infrastructure to rapidly prototype and validate new ideas - Transform theoretical insights into practical solutions that can handle the complexities of real-world robotics applications About the team 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 innovative 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, Leo Security
US, WA, Seattle
Amazon Leo is a constellation of Low Earth Orbit satellites that will provide low-latency, high-speed broadband network connectivity to unserved and underserved communities around the world. We are looking for an Applied Scientist to join the founding cohort of the Engineering and R\&D team within Leo Infrastructure and IP Security. The team defends the manufacturing lines, launch sites, and global ground infrastructure behind the constellation from the most sophisticated threat actors on the planet. The data is unlike anything you have worked with: badge and door-access events, asset movement, network telemetry, and industrial control signals from factories, ground stations, and launch facilities, all of which must be modeled, baselined, and defended. You will build the statistical and behavioral models that separate threat actor behavior from the noise of a global operation, and the privacy-preserving data representations that let detection science scale without exposing sensitive data. This is an R\&D role with a production mandate: every model you build becomes part of the system Leo's security teams use to protect the constellation. #### Export Control Requirement Due to applicable export control laws and regulations, candidates must be a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum. Key job responsibilities - Build behavioral and statistical models that baseline normal activity across heterogeneous security telemetry, including specialized industrial-control and factory-floor data sources, so detections extend to new environments with low false-positive rates. - Design privacy-preserving representations of sensitive security data, and verify that models and detections tuned against them remain accurate against the real data — turning data-protection guarantees into measurable, provable properties rather than assertions. - Define the methodology and own the analysis for difficult, loosely defined problems: gather complex data across domains, select the right techniques from a range of data science methods, and justify your approach with evidence. - Develop the metrics and evaluation frameworks that measure model and detection performance against threat actor behavior before a model is trusted in production. - Contribute to the team's neurosymbolic reasoning platform, adapting state-of-the-art techniques from the literature and shipping components at production quality. - Document your work with the rigor of a peer-reviewed publication, and communicate results clearly to both scientific and security-operations audiences. A day in the life You will move between analysis and production in the same week: profiling a telemetry source the team has never modeled, establishing what normal looks like for it, and shipping the baseline as a component detections build on. Security engineers on your team translate threat intelligence into the adversary behaviors that matter; you build and tune the models that detect those behaviors and evaluate model performance against them. You might spend a morning chasing a false-positive pattern to its statistical root cause, and the afternoon verifying that an anonymized dataset still preserves the signal a detection depends on. You will work semi-autonomously with guidance from senior scientists, backtest candidate detections against retained telemetry, and deliver scientific artifacts that ship. About the team Leo Infrastructure and IP Security protects the people, facilities, hardware, and supply chain behind a global satellite constellation. The Engineering and R\&D team within this organization builds the platforms and tooling the security pillar teams operate on, moving security operations from manual triage to correlation-based detection, automated response, and agentic AI. The team is composed of applied scientists, software engineers, and security engineers working across physical and digital security domains. #### 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, Amazon Transportation
GB, London
Amazon’s Middle Mile Science group is looking for an Applied Scientist to build machine learning and optimization models to support pricing and revenue management of its external freight business. This includes the development of novel forecasting and dynamic pricing models, as well as the application of causal inference and artificial intelligence techniques, to improve marketplace services and execution for our customers. The Middle Mile Science group develops optimization and machine learning systems that power Amazon's freight transportation network, from network design and pricing to real-time load planning and capacity utilization. The scale of Amazon's fulfillment operations requires robust transportation networks that minimize cost while meeting all customer deadlines. Real-time execution depends on state-of-the-art optimization and artificial intelligence to coordinate thousands of operators and drivers. This includes shipper-facing and carrier-facing marketplace algorithms as well as network planning and optimization tools. Amazon often finds that existing techniques do not match our unique business needs,driving the innovation of new approaches and algorithms. As an Applied Scientist responsible for middle mile transportation, you will be working closely with different teams including business leaders and engineers to design and build scalable products operating across multiple transportation modes. You will create experiments and prototype implementations of new learning algorithms and prediction techniques. You will have exposure to top level leadership to present findings of your research. You will also work closely with other scientists and engineers to implement your models within our production system. You will implement solutions that are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility, and make decisions that affect the way we build and integrate algorithms across our product portfolio. About the team Our Middle Mile Marketplace Science team builds the algorithms for Amazon’s rapidly growing freight marketplace. Amazon contracts with 3P shippers and a network of independent carriers, using a mix of contract structures with varying service and risk profiles. Our work focuses on mechanisms and learning algorithms to optimize pricing and matching in this complex marketplace, and continually improve the experience for carriers and shippers. This is an area with many challenging problems and a huge business impact for Amazon!
Quantum Fab R&D Scientist, Amazon Center for Quantum Computing
US, CA, Pasadena
The Amazon Center for Quantum Computing in Pasadena, CA, is looking to hire a Fabrication R&D Scientist with experience in semiconductor process development who will aid in Amazon’s effort to bring cloud quantum computing services to its worldwide customer base. You will join a multi-disciplinary team of scientists, and hardware and software engineers working at the forefront of quantum computing. Through your work inside and outside of the cleanroom environment in the fabrication research and development group, you will solve problems related to developing next-generation quantum processors. Key job responsibilities Candidates must have a demonstrated background in sound scientific and engineering principles, and must have excellent data analysis, bias for action, problem solving, and communication skills, and be highly motivated and curious to research and learn new technical topics as needed. As a Fab R&D scientist you will be expected to work on new ideas and stay abreast of novel approaches in fabricating and packaging superconducting quantum processors. Working effectively within a team environment is critical. A day in the life The candidate will develop novel technologies using micro-/nano-fabrication techniques inside the cleanroom (independently or in collaboration with other scientists and engineers) for next-generation quantum computing. Outside the cleanroom, the candidate will plan experiments, analyze data, and conceive future innovations. About the team Candidates must have a demonstrated background in sound scientific and engineering principles, and must have excellent data analysis, bias for action, problem solving, and communication skills, and be highly motivated and curious to research and learn new technical topics as needed. As a Fab R&D scientist you will be expected to work on new ideas and stay abreast of novel approaches in fabricating and packaging superconducting quantum processors. Working effectively within a team environment is critical. Diverse Experiences Amazon values diverse experiences. Even if you do not meet all 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. Work/Life Balance Our team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives. 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. 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. Key job responsibilities Responsibilities include developing and optimizing processes to fabricate high-coherence superconducting qubits; developing advanced 3DI interconnect and routing technologies for integrating superconducting quantum technologies; analyzing inline metrology and electrical test data; developing and maintaining integration documentation, design rules, and standard operating procedures; interacting with project leads to provide feedback that continuously improves different processes; staying updated with the latest advancements and industry trends in process integration and apply knowledge to improve processes and drive innovation providing technical guidance and support to junior colleagues, fostering a collaborative and knowledge-sharing work environment.
Senior Applied Scientist, Leo Security
US, WA, Seattle
Amazon Leo is a constellation of Low Earth Orbit satellites that will provide low-latency, high-speed broadband network connectivity to unserved and underserved communities around the world. We are looking for an Applied Scientist to be a founding scientist on the Engineering and R\&D team within Leo Infrastructure and IP Security. The team defends the manufacturing lines, launch sites, and global ground infrastructure behind the constellation from the most sophisticated threat actors on the planet. These requirements create open scientific problems at the intersection of agentic AI, real-time stream processing, graph-based reasoning, and behavioral analytics. You will build the science behind a neurosymbolic reasoning platform and the models that detect the behavior of sophisticated threat actors. This is an R\&D role with a production mandate, where you define the problem rather than solve a pre-scoped one, and every model, detection, and agent workflow you build becomes the system Leo's security teams use to protect the constellation. #### Export Control Requirement Due to applicable export control laws and regulations, candidates must be a U.S. citizen or national, U.S. permanent resident (i.e., current Green Card holder), or lawfully admitted into the U.S. as a refugee or granted asylum. Key job responsibilities - Design and implement scalable, production-grade neurosymbolic systems that integrate symbolic reasoning over graph-based knowledge representations with LLM agents to deliver reliable, verifiable security outcomes. - Design and run reinforcement learning and fine-tuning pipelines (GRPO, PPO, DPO) to optimize language models for security reasoning, triage, and detection-authoring tasks. - Build behavioral and statistical models that detect threat actor behavior, and design the evaluation frameworks that measure model performance against that behavior before trusting a model in production. - Design and build multi-agent systems that autonomously triage, enrich, and contain security events, including the constrained reasoning, safety guardrails, and validation mechanisms that make automated decisions trustworthy at scale. - Own the end-to-end science lifecycle, from research and experimentation through production deployment, defining the metrics that measure system performance and real-world security impact. - Advance the state of the art through publications at top-tier venues, patents, or open-source contributions, and shape the scientific agenda and research culture from day one. A day in the life You will move between research and production in the same week: framing an ambiguous security problem as a scientific question, prototyping an approach, and partnering with software engineers to ship it as a capability the platform runs continuously. Security engineers on your team translate threat intelligence into the adversary behaviors that matter; you build the models that detect those behaviors and evaluate model performance against them. You will obsess over the two latencies that define the platforms, the time from event to detection and the time from detection to containment action, and design agents and detections that drive both down. You will backtest candidate detections against retained telemetry, review evaluation results before a model or agent capability graduates to automated execution, and deliver scientific artifacts that ship. About the team Leo Infrastructure and IP Security protects the people, facilities, hardware, and supply chain behind a global satellite constellation. The Engineering and R\&D team within this organization builds the platforms and tooling the security pillar teams operate on, moving security operations from manual triage to correlation-based detection, automated response, and agentic AI. The team is composed of applied scientists, software engineers, and security engineers working across physical and digital security domains. #### 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.
Sr. Applied Scientist, Classification and Policy Platform
US, WA, Seattle
Ever wonder how you can keep the world’s largest selection also the world’s safest and legally compliant selection? Then come join a team with the charter to monitor and classify the billions of items in the Amazon catalog to ensure compliance with various legal regulations. The Classification and Policy Platform team is looking for Sr. Applied Scientists to build technology to automatically monitor the billions of products on the Amazon platform. The software and processes built by this team are a critical component of building a catalog that our customers trust. You will have an opportunity to work with cutting edge machine learning algorithms on large datasets. You will need to build Amazon scale applications running on Amazon Cloud that both leverage and create new technologies to process large volumes of data that derive patterns and conclusions from the data. We are looking for highly motivated applied scientists and engineers interested in delivering the next level of innovation to product search for Amazon. As an Applied Scientist on the CPP team, you will be responsible for working across backend, client, business development, and data engineering teams to coordinate deep-dives, inform roadmaps, visualize metrics, and create predictive models to determine how we can best serve our customers. Responsibilities include: - Designing and implementing new features and machine learned models, including the application of state-of-art deep learning to solve search matching and ranking problems, including filtering, new content indexing, and apply document understanding - Conducting and coordinating process development leading to improved and streamlined processes for model development. Strong customer focus is essential - Working closely with Product Managers to expand depth of our product insights with data, create a variety of experiments, and determine the highest-impact projects to include in planning roadmaps - Providing technical and scientific guidance to your team members - Communicating effectively with senior management as well as with colleagues from science, engineering, and business backgrounds - Being a cultural leader that ensures teams are collecting, understanding, and using data to inform every decision that impacts our customers The successful candidate will have an established background in developing customer-facing experiences, a strong technical ability, a start-up mentality, excellent project management skills, and great communication skills. Amazon Science gives you insight into the company’s approach to customer-obsessed scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It’s the company’s ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields. Our scientists continue to publish, teach, and engage with the academic community, in addition to utilizing our working backwards method to enrich the way we live and work. Please visit https://www.amazon.science for more information.
Research Scientist, Fauna
US, NY, New York
We are seeking an Research 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
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