A graphic shows a simulation of what a VR guided experience might look like, it features colored circles, a humanoid face, and other features
TRIPP is an Alexa Fund portfolio company that is exploring how virtual reality can be combined with meditation. The company's CEO and co-founder Nanea Reeves noted that the VR experiences "are deliberately psychedelic. You find yourself inside an atom or floating in space."
TRIPP

TRIPP explores the potential of virtual reality–powered meditation

Alexa Fund portfolio company’s science-led program could change how we approach mental wellness — and how we use VR.

(Editor’s note: This article is the latest installment in a series by Amazon Science delving into the science behind products and services of companies in which Amazon has invested. The Alexa Fund participated in TRIPP’s $11.2M Series A extension funding round in June 2022.)

With meditation soaring in popularity and the virtual reality (VR) industry booming, Alexa Fund portfolio company TRIPP is at the confluence of two powerful trends: mental well-being and VR. TRIPP is a digital wellness program that uses VR headsets to immerse users in breathing meditation experiences.

The idea to meld meditation and VR first occurred to TRIPP CEO and co-founder Nanea Reeves in 2017 when she, a lifelong practitioner of meditation with a 15-year career in the gaming industry, was experimenting with the medium by building a solitaire game in VR.

This graphic shows a potential visualization from the VR app TRIPP, it includes a planet floating in space against a background featuring stars and bright colors
TRIPP CEO Nanea Reeves said she was inspired by the work of Giuseppe Riva, a neuropsychologist. “We wondered if we could create environments that make you go, ‘Oh, wow!’ and give you a lift,” Reeves explains.
TRIPP

“The way I felt exploring VR was even more interesting to me than the actual development,” Reeves says. Her interest developed into a deep curiosity about the psychological effects of VR, and she began searching the scientific literature.

In addition to studying VR in medical and mental health use cases, she discovered work by Giuseppe Riva, a neuropsychologist whose research has shown that VR can elicit emotions such as awe and, in turn, influence people’s well-being, agency, and perceptions of themselves.

“Inspired by Giuseppe’s research, we wondered if we could create environments that make you go, ‘Oh, wow!’ and give you a lift,” Reeves explains. That became her impetus to found TRIPP in 2017, pursuing the hypothesis that, by stimulating experiences through VR, people may gain some agency over their emotions.

Riva’s work identified several aspects of VR that made it particularly effective for evoking awe, including its immersive nature and the complexity and scale of virtual environments.

“We started leaning into that, and we started to play with scale in our designs,” says Reeves.

In 2019, TRIPP launched its award-winning wellness application, TRIPP, in VR. The application offers immersive mindfulness experiences and, to date, has delivered nearly 6 million wellness sessions. TRIPP continues to work closely with neuroscience and psychiatry advisors through PsyAssist to design and evaluate their experiences and with a host of researchers who are studying its potential uses.

A recent clinical trial suggested that TRIPP might positively influence well-being and mood in cancer patients, and ongoing projects are assessing whether TRIPP can help people in recovery from substance use disorders or anxiety and pain control, among other initiatives.

“With some of the early data coming in, it seems very promising that tools like TRIPP might have a positive impact,” Reeves says, “but we are still only at the beginning of what may be possible with VR.”

Amazon Science spoke with Reeves about the motivation for TRIPP, its roots in science, and the implications for what it can achieve with VR.

  1. Q. 

    Why take meditation virtual?

    A. 

    It’s actually a super native case for VR, because the immersive quality allows you to unplug. You can’t look at your phone by nature of the immersion. I was blown away by how I felt moving in and out of VR — the feeling of respite.

    A lot of the early VR experiences simulated environments that made you terrified, like walking a plank or standing at the edge of a cliff. And it occurred to me: if we could scare people so easily, could we trigger other emotional changes that are beneficial?

    Our approach is to use immersion to drive a deeper connection to self-contemplative thoughts. You’re immersed in this psychologically safe container that is designed to capture your awareness, to allow you to be present and connect to self. With VR, it’s not just an audio file guiding you toward connecting with your breath. We can show you your breath, like star crystals coming in and out of your mouth.

    Some of the early offerings thought VR was really only for gaming. When we first got TRIPP on Oculus, they didn’t know where to put us because they didn’t have a relaxation genre then. We were pretty buried in the store. But we started to get a little bit of traction, and we soon had surprisingly regular usage over time. VR has this problem where you go in, you go, “Wow, that was amazing!” and then it's in your closet. You never pick it up again. When we were designing the product, we knew we had to build for repeat usage. So, we built it procedurally, and now we can update it from the server and add new content regularly.

  2. Q. 

    How is science leading the design and development of TRIPP?

    A. 

    I started by looking at the research investigating VR’s effect on the brain, largely by neuroscientists and behavioral therapists exploring mental health and medical use cases for VR. Most of them focused on simulation, like simulated exposure therapy. But I wondered if, instead of simulating something, could we stimulate responses? I took that question to the researchers working on VR and its effects on mental well-being. We started digging into the research and then, based on the research data, designed VR experiences intended to trigger states of wonder and awe. We tried them out on people and captured some physiological data like heart rate and EEG to see if the experiences were directionally achieving the effect we wanted.

    We stay very grounded in research-driven design choices. We’re a bit edgy. Rather than mimicking natural environments, the experiences are deliberately psychedelic. You find yourself inside an atom or floating in space. First, we tried things like a waterfall or a beach, but when we tested them, they didn’t feel good. I found some research describing how sensory dissonance in synthetic natural environments can create a stress response. Your brain goes, “Well, it looks like a beach, but I don’t smell the ocean. So what’s wrong with this environment?” We realized we had to create environments for which you have no mental model. So we said, “OK, let’s put you in a cosmic flotation tank, whatever that means, because no one knows what space smells like.”

    We’re also starting an enterprise program to support employee wellness and team-building with a hybrid workforce, but also with a focus on using the metaverse for driving ideation and innovation. Can we use these otherworldly environments to spark creativity?
    Nanea Reeves

    After we launched, we started collecting data on mood and emotional state in the live user sessions via self-reported surveys that are based on what they use in mental health research. We bookended our sessions with users, basically asking “How do you feel?” before and after each session. We did things like randomizing the order of the response selections to control against position bias. Now, we have data collected from close to 6 million sessions that we can slice and dice by the time of day and, for a percentage of our audience who opted in, age, gender, and location. It’s become a meaningful body of data that we can share with researchers once it has been de-identified. We also work with researchers who want to study TRIPP and its potential applications. It’s been fascinating to work with that community.

    One example is this group in Germany working with cancer patients undergoing surgery, looking at the effects of TRIPP sessions on their quality of life, well-being, and mood. This study was published in Nature’s Scientific Reports. Participation was good, and patients who used TRIPP had lower heart rates and breathing rates after their sessions. They had improved scores on their mood and emotion surveys after the sessions too. What the study shows us is that VR-based relaxation is a viable option and may be beneficial for cancer patients undergoing surgery. Of course, we don’t make any therapeutic claims until we have a tremendous amount of evidence to support those claims.

    You can find other published data and scientific reports examining TRIPP’s effects on adolescents and its use in palliative care. And we’re working with researchers who are looking at whether TRIPP could help people experiencing addiction and rehab, chemotherapy, severe mental illness, anxiety, and pain. Researchers are also using TRIPP to ease anxiety and help people prepare for ketamine-assisted therapy, so they get the most out of their treatment. I feel very motivated to see how we can help and participate in these research initiatives.

  3. Q. 

    How might TRIPP change how we use VR, beyond its medical applications?

    A. 

    Earlier this year, we acquired EvolVR, which holds live group meditations. Several hundred avatars attend the most popular conversations. People really open up. Skip Rizzo, PhD, a renowned researcher in the field and an advisor to TRIPP, did a pilot study and found that people suffering from PTSD were more open and honest with an avatar. We want to further investigate this as there’s something about the “digital veil” of VR where you don’t feel the judgment of being seen by other people. I think this is a wonderful use case for the metaverse.

    We’re also starting an enterprise program to support employee wellness and team-building with a hybrid workforce, but also with a focus on using the metaverse for driving ideation and innovation. Can we use these otherworldly environments to spark creativity?

    It’s also fascinating to think about the gig economy that could emerge from the metaverse — similar to what first emerged from mobile computing. For example, I met a woman at one of our live group meditation events in the metaverse who’s earning a living as one of the top world-builders in Altspace VR. She’s a mother of five who has never worked in tech before. She’s now a programmer, building these virtual worlds.

    We’re only beginning to explore the potential of VR. It’s like the early days of mobile. Initially, no one thought we’d want to play games or even text message on our cell phones. Now, for the past decade, we have been walking around with our heads down staring at these phone screens nonstop. What kind of innovation will happen in a future when XR glasses are ubiquitous and allow us to experience the world around us in an entirely new and adaptive way?

Related content

IN, KA, Bengaluru
Alexa+ is Amazon’s next-generation, AI-powered virtual assistant. Building on the original Alexa, it uses generative AI to deliver a more conversational, personalised, and effective experience. Alexa Sensitive Content Intelligence (ASCI) team is developing responsible AI (RAI) solutions for Alexa+, empowering it to provide useful information responsibly. The team is currently looking for Senior Applied Scientists with a strong background in NLP and/or CV to design and develop ML solutions in the RAI space using generative AI across all languages and countries. A Senior Applied Scientist will be a tech lead for a team of exceptional scientists to develop novel algorithms and modeling techniques to advance the state of the art in NLP or CV related tasks. You will work in a hybrid, fast-paced organization where scientists, engineers, and product managers work together to build customer facing experiences. You will collaborate with and mentor other scientists to raise the bar of scientific research in Amazon. Your work will directly impact our customers in the form of products and services that make use of speech, language, and computer vision technologies. We are looking for a leader with strong technical experiences a passion for building scientific driven solutions in a fast-paced environment. You should have good understanding of Artificial Intelligence (AI), Natural Language Understanding (NLU), Machine Learning (ML), Dialog Management, Automatic Speech Recognition (ASR), and Audio Signal Processing where to apply them in different business cases. You leverage your exceptional technical expertise, a sound understanding of the fundamentals of Computer Science, and practical experience of building large-scale distributed systems to creating reliable, scalable, and high-performance products. In addition to technical depth, you must possess exceptional communication skills and understand how to influence key stakeholders. You will be joining a select group of people making history producing one of the most highly rated products in Amazon's history, so if you are looking for a challenging and innovative role where you can solve important problems while growing as a leader, this may be the place for you. Key job responsibilities You'll lead the science solution design, run experiments, research new algorithms, and find new ways of optimizing customer experience. You set examples for the team on good science practice and standards. Besides theoretical analysis and innovation, you will work closely with talented engineers and ML scientists to put your algorithms and models into practice. Your work will directly impact the trust customers place in Alexa, globally. You contribute directly to our growth by hiring smart and motivated Scientists to establish teams that can deliver swiftly and predictably, adjusting in an agile fashion to deliver what our customers need. A day in the life You will be working with a group of talented scientists on researching algorithm and running experiments to test scientific proposal/solutions to improve our sensitive contents detection and mitigation. This will involve collaboration with partner teams including engineering, PMs, data annotators, and other scientists to discuss data quality, policy, and model development. You will mentor other scientists, review and guide their work, help develop roadmaps for the team. You work closely with partner teams across Alexa to deliver platform features that require cross-team leadership. About the hiring group About the team The mission of the Alexa Sensitive Content Intelligence (ASCI) team is to (1) minimize negative surprises to customers caused by sensitive content, (2) detect and prevent potential brand-damaging interactions, and (3) build customer trust through appropriate interactions on sensitive topics. The term “sensitive content” includes within its scope a wide range of categories of content such as offensive content (e.g., hate speech, racist speech), profanity, content that is suitable only for certain age groups, politically polarizing content, and religiously polarizing content. The term “content” refers to any material that is exposed to customers by Alexa (including both 1P and 3P experiences) and includes text, speech, audio, and video.
US, WA, Bellevue
Amazon is looking for a Principal Applied Scientist world class scientists to join its AWS Fundamental Research Team working within a variety of machine learning disciplines. This group is entrusted with developing core machine learning solutions for AWS services. At the AWS Fundamental Research Team you will invent, implement, and deploy state of the art machine learning algorithms and systems. You will build prototypes and explore conceptually large scale ML solutions across different domains and computation platforms. You will interact closely with our customers and with the academic community. You will be at the heart of a growing and exciting focus area for AWS and work with other acclaimed engineers and world famous scientists. About the team About the team Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why 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.
US, NJ, Newark
At Audible, we believe stories have the power to transform lives. It’s why we work with some of the world’s leading creators to produce and share audio storytelling with our millions of global listeners. We are dreamers and inventors who come from a wide range of backgrounds and experiences to empower and inspire each other. Imagine your future with us. ABOUT THIS ROLE As an Applied Scientist, you will solve large complex real-world problems at scale, draw inspiration from the latest science and technology to empower undefined/untapped business use cases, delve into customer requirements, collaborate with tech and product teams on design, and create production-ready models that span various domains, including Machine Learning (ML), Artificial Intelligence (AI), Natural Language Processing (NLP), Reinforcement Learning (RL), real-time and distributed systems. As an Applied Scientist on our AI Acceleration Team, you will be at the forefront of transforming how Audible harnesses the power of AI to enhance productivity, unlock new value, and reimagine how we work. In this unique role, you'll apply ML/AI approaches to solve complex real-world problems while helping build the blueprint for how Audible works with AI. ABOUT YOU You are passionate about applying scientific approaches to real business challenges, with deep expertise in Machine Learning, Natural Language Processing, GenAI, and large language models. You thrive in collaborative environments where you can both build solutions and empower others to leverage AI effectively. You have a track record of developing production-ready models that balance scientific excellence with practical implementation. You're excited about not just building AI solutions, but also creating frameworks, evaluation methodologies, and knowledge management systems that elevate how entire organizations work with AI. As an Applied Scientist, you will... - Design and implement innovative AI solutions across our three pillars: driving internal productivity, building the blueprint for how Audible works with AI, and unlocking new value through ML & AI-powered product features - Develop machine learning models, frameworks, and evaluation methodologies that help teams streamline workflows, automate repetitive tasks, and leverage collective knowledge - Enable self-service workflow automation by developing tools that allow non-technical teams to implement their own solutions - Collaborate with product, design and engineering teams to rapidly prototype new product ideas that could unlock new audiences and revenue streams - Build evaluation frameworks to measure AI system quality, effectiveness, and business impact - Mentor and educate colleagues on AI best practices, helping raise the AI fluency across the organization ABOUT AUDIBLE Audible is the leading producer and provider of audio storytelling. We spark listeners’ imaginations, offering immersive, cinematic experiences full of inspiration and insight to enrich our customers daily lives. We are a global company with an entrepreneurial spirit. We are dreamers and inventors who are passionate about the positive impact Audible can make for our customers and our neighbors. This spirit courses throughout Audible, supporting a culture of creativity and inclusion built on our People Principles and our mission to build more equitable communities in the cities we call home.
IN, TS, Hyderabad
Are you fascinated by the power of Natural Language Processing (NLP) and Large Language Models (LLM) to transform the way we interact with technology? Are you passionate about applying advanced machine learning techniques to solve complex challenges in the e-commerce space? If so, Amazon's International Seller Services team has an exciting opportunity for you as an Applied Scientist. At Amazon, we strive to be Earth's most customer-centric company, where customers can find and discover anything they want to buy online. Our International Seller Services team plays a pivotal role in expanding the reach of our marketplace to sellers worldwide, ensuring customers have access to a vast selection of products. As an Applied Scientist, you will join a talented and collaborative team that is dedicated to driving innovation and delivering exceptional experiences for our customers and sellers. You will be part of a global team that is focused on acquiring new merchants from around the world to sell on Amazon’s global marketplaces around the world. Join us at the Central Science Team of Amazon's International Seller Services and become part of a global team that is redefining the future of e-commerce. With access to vast amounts of data, technology, and a diverse community of talented individuals, you will have the opportunity to make a meaningful impact on the way sellers engage with our platform and customers worldwide. Together, we will drive innovation, solve complex problems, and shape the future of e-commerce. Please visit https://www.amazon.science for more information Key job responsibilities - Apply your expertise in LLM models to design, develop, and implement scalable machine learning solutions that address complex language-related challenges in the international seller services domain. - Collaborate with cross-functional teams, including software engineers, data scientists, and product managers, to define project requirements, establish success metrics, and deliver high-quality solutions. - Conduct thorough data analysis to gain insights, identify patterns, and drive actionable recommendations that enhance seller performance and customer experiences across various international marketplaces. - Continuously explore and evaluate state-of-the-art NLP techniques and methodologies to improve the accuracy and efficiency of language-related systems. - Communicate complex technical concepts effectively to both technical and non-technical stakeholders, providing clear explanations and guidance on proposed solutions and their potential impact. - Mentor and guide team of Applied Scientists from technical and project advancement stand point - Contribute research to science community and conference quality level papers.
US, WA, Seattle
We are open to hiring candidates to work out of one of the following locations: Seattle, WA, USA Are you interested in building Agentic AI solutions that solve complex builder experience challenges with significant global impact? The Security Tooling team designs and builds high-performance AI systems using LLMs and machine learning that identify builder bottlenecks, automate security workflows, and optimize the software development lifecycle—empowering engineering teams worldwide to ship secure code faster while maintaining the highest security standards. As a Senior Applied Scientist on our Security Tooling team, you will focus on building state-of-the-art ML models to enhance builder experience and productivity. You will identify builder bottlenecks and pain points across the software development lifecycle, design and apply experiments to study developer behavior, and measure the downstream impacts of security tooling on engineering velocity and code quality. Our team rewards curiosity while maintaining a laser-focus on bringing products to market that empower builders while maintaining security excellence. 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 builder experience and security automation, you have the opportunity to work together with a diverse and talented team of scientists, engineers, and product managers and collaborate with other teams. This role offers a unique opportunity to work on projects that could fundamentally transform how builders interact with security tools and how organizations balance security requirements with developer productivity. Key job responsibilities • Design and implement novel AI/ML solutions for complex security challenges and improve builder experience • Drive advancements in machine learning and science • Balance theoretical knowledge with practical implementation • Navigate ambiguity and create clarity in early-stage product development • Collaborate with cross-functional teams while fostering innovation in a collaborative work environment to deliver impactful solutions • Design and execute experiments to evaluate the performance of different algorithms and models, and iterate quickly to improve results • Establish best practices for ML experimentation, evaluation, development and deployment You’ll need a strong background in AI/ML, proven leadership skills, and the ability to translate complex concepts into actionable plans. You’ll also need to effectively translate research findings into practical solutions. A day in the life • Integrate ML models into production security tooling with engineering teams • Build and refine ML models and LLM-based agentic systems that understand builder intent • Create agentic AI solutions that reduce security friction while maintaining high security standards • Prototype LLM-powered features that automate repetitive security tasks • Design and conduct experiments (A/B tests, observational studies) to measure downstream impacts of tooling changes on engineering productivity • Present experimental results and recommendations to leadership and cross-functional teams • Gather feedback from builder communities to validate hypotheses About the team 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.
US, WA, Seattle
Amazon Music is an immersive audio entertainment service that deepens connections between fans, artists, and creators. From personalized music playlists to exclusive podcasts, concert livestreams to artist merch, Amazon Music is innovating at some of the most exciting intersections of music and culture. We offer experiences that serve all listeners with our different tiers of service: Prime members get access to all the music in shuffle mode, and top ad-free podcasts, included with their membership; customers can upgrade to Amazon Music Unlimited for unlimited, on-demand access to 100 million songs, including millions in HD, Ultra HD, and spatial audio; and anyone can listen for free by downloading the Amazon Music app or via Alexa-enabled devices. Join us for the opportunity to influence how Amazon Music engages fans, artists, and creators on a global scale. Key job responsibilities - Work backwards from customer problems to research and develop novel machine learning solutions for music and podcast recommendations. Through A/B testing and online experiments done hand-in-hand with engineering teams, you'll implement and validate your ideas and solutions. - Advocate solutions and communicate results, insights and recommendations to stakeholders and partners. - Produce innovative research on recommender systems that shapes the field and meets the high standards of peer-reviewed publications. You'll cement your team's reputation as thought leaders pioneering new recommenders. Stay current with advancements in the field, adapting latest in literature to build efficient and scalable models A day in the life Lead innovation in AI/ML to shape Amazon Music experiences for millions. Develop state of the art models leveraging and advancing the latest developments in machine learning and genAI. Collaborate with talented engineers and scientists to guide research and build scalable models across our audio portfolio - music, podcasts, live streaming, and more. Drive experiments and rapid prototyping, leveraging Amazon's data at scale. Innovate daily alongside world-class teams to delight customers worldwide through personalization. About the team The team is responsible for models that underly Amazon Music’s recommendations content types (music, podcasts, audiobooks), sequencing models for algorithmic stations across mobile, web and Alexa, ranking models for the carousels and Page strategy on Amazon Music surfaces, and Query Understanding for conversational flow and recommendations. You will collaborate with a team of product managers, applied scientists and software engineers delivering meaningful recommendations, personalized for each of the millions of customers using Amazon Music globally. As a scientist on the team, you will be involved in every aspect of the development lifecycle, from idea generation and scientific research to development and deployment of advanced models. You will work closely with engineering to realize your scientific vision.
US, WA, Seattle
We are looking for a talented, organized, and customer-focused applied researchers to join our Pricing Optimization science group, with a charter to measure, refine, and launch customer-obsessed improvements to our algorithmic pricing and promotion models across all products listed on Amazon. This role requires an individual with exceptional machine learning modeling and architecture expertise, excellent cross-functional collaboration skills, business acumen, and an entrepreneurial spirit. We are looking for an experienced innovator, who is a self-starter, comfortable with ambiguity, demonstrates strong attention to detail, and has the ability to work in a fast-paced and ever-changing environment. Key job responsibilities * See the big picture. Understand and influence the long term vision for Amazon's science-based competitive, perception-preserving pricing techniques * Build strong collaborations. Partner with product, engineering, and science teams within Pricing & Promotions to deploy machine learning price estimation and error correction solutions at Amazon scale * Stay informed. Establish mechanisms to stay up to date on latest scientific advancements in machine learning, neural networks, natural language processing, probabilistic forecasting, and multi-objective optimization techniques. Identify opportunities to apply them to relevant Pricing & Promotions business problems * Keep innovating for our customers. Foster an environment that promotes rapid experimentation, continuous learning, and incremental value delivery. * Successfully execute & deliver. Apply your exceptional technical machine learning expertise to incrementally move the needle on some of our hardest pricing problems. A day in the life We are hiring an applied scientist to drive our pricing optimization initiatives. We drive cross-domain and cross-system improvements through: * invent and deliver price optimization, simulation, and competitiveness tools for Amazon merchants. * shape and extend our RL optimization platform - a pricing centric tool that automates the optimization of various system parameters and price inputs. * Error detection and price quality guardrails at scale. * Identifying opportunities to optimally price across systems and contexts (marketplaces, request types, event periods) Price is a highly relevant input into Stores architectures, and is highly relevant to the customer; this role creates the opportunity to drive extremely large impact (measured in Bs not Ms), but demands careful thought and clear communication.
SE, Stockholm
Come build the future of entertainment with us. Are you interested in shaping the future of movies and television? Do you want to define the next generation of how and what Amazon customers are watching? Prime Video is a premium streaming service that offers customers a vast collection of TV shows and movies - all with the ease of finding what they love to watch in one place. We offer customers thousands of popular movies and TV shows including Amazon Originals and exclusive licensed content to exciting live sports events. We also offer our members the opportunity to subscribe to add-on channels which they can cancel at anytime and to rent or buy new release movies and TV box sets on the Prime Video Store. Prime Video is a fast-paced, growth business - available in over 200 countries and territories worldwide. The team works in a dynamic environment where innovating on behalf of our customers is at the heart of everything we do. If this sounds exciting to you, please read on. The Prime Video Sye Protocol team is looking for an Applied Scientist. This person will deliver features that automatically detect and prevent video quality issues before they reach millions of customers worldwide. You will lead the design of models that scale to very large quantities of video data across multiple dimensions. You will embody scientific rigor, designing and executing experiments to demonstrate the technical effectiveness and business value of your methods. You will work alongside engineering teams to deliver your research into production systems that ensure premium streaming experiences for customers globally. You will have demonstrated technical, teamwork and communication skills, and a motivation to deliver customer value from your research. Our team offers exceptional opportunities for you to grow your technical and non-technical skills and make a global impact. Key job responsibilities - Design, prototype and test many possible hypotheses in a high-ambiguity environment, making use of both quantitative analysis and business judgement to solve complex video defect detection challenges. - Collaborate with software engineers to integrate successful experimental results into Prime Video wide processes and production systems that operate at scale with minimal computational overhead. - Communicate results and insights to both technical and non-technical audiences, including presentations and written reports to stakeholders across engineering, operations, and content teams. A day in the life Your typical day starts investigating overnight video quality alerts and developing breakthrough detection algorithms. You'll collaborate with engineering teams on production deployment, analyze video data to uncover quality patterns, and work with transformers and video language models. About the team You'll join a team focused on delivering premium video experiences through scientific innovation. We build machine learning systems that automatically detect video quality issues across our global streaming platform, collaborating closely with engineering, operations, and content teams to solve video analysis challenges while ensuring customers never experience poor quality. Our team partners with leading universities to develop solutions and advance computer vision and machine learning techniques. We value scientific rigor whilst staying customer-focused, encouraging both innovative and practical solutions that scale globally. There are opportunities for high-impact publications and patent development that advance the entire field.
US, MA, Boston
AI is the most transformational technology of our time, capable of tackling some of humanity’s most challenging problems. That is why Amazon is investing in generative AI (GenAI) and the responsible development and deployment of large language models (LLMs) across all of our businesses. Come build the future of human-technology interaction with us. We are looking for a Research Scientist with strong technical skills which includes coding and natural language processing experience in dataset construction, training and evaluating models, and automatic processing of large datasets. You will play a critical role in driving innovation and advancing the state-of-the-art in natural language processing and machine learning. You will work closely with cross-functional teams, including product managers, language engineers, and other scientists. Key job responsibilities Specifically, the Research Scientist will: • Ensure quality of speech/language/other data throughout all stages of acquisition and processing, including data sourcing/collection, ground truth generation, normalization, transformation, cross-lingual alignment/mapping, etc. • Clean, analyze and select speech/language/other data to achieve goals • Build and test models that elevate the customer experience • Collaborate with colleagues from science, engineering and business backgrounds • Present proposals and results in a clear manner backed by data and coupled with actionable conclusions • Work with engineers to develop efficient data querying infrastructure for both offline and online use cases
US, VA, Arlington
Are you fascinated by the power of Large Language Models (LLM) and Artificial Intelligence (AI) to transform the way we learn and interact with technology? Are you passionate about applying advanced machine learning (ML) techniques to solve complex challenges in the cloud learning space? If so, AWS Training & Certification (T&C) team has an exciting opportunity for you as an Applied Scientist. At AWS T&C, we strive to be leaders in not only how we learn about the latest AI/ML development and AWS services, but also how the same technologies transform the way we learn about them. As an Applied Scientist, you will join a talented and collaborative team that is dedicated to driving innovation and delivering exceptional experiences in our Skill Builder platform for both new learners and seasoned developers. You will be a part of a global team that is focused on transforming how people learn. The position will interact with global leaders and teams across the globe as well as different business and technical organizations. Join us at the AWS T&C Science Team and become a part of a global team that is redefining the future of cloud learning. With access to vast amounts of data, exciting new technology, and a diverse community of talented individuals, you will have the opportunity to make a meaningful impact on the ways how worldwide learners engage with our learning system and builders develop on our platform. Together, we will drive innovation, solve complex problems, and shape the future of future-generation cloud builders. Please visit https://skillbuilder.awsto learn more. Key job responsibilities - Apply your expertise in LLM to design, develop, and implement scalable machine learning solutions that address challenges in discovery and engagement for our international audiences. - Collaborate with cross-functional teams, including software engineers, data engineers, scientists, and product managers, to define project requirements, establish success metrics, and deliver high-quality solutions. - Conduct thorough data analysis to gain insights, identify patterns, and drive actionable recommendations that enhance operational performance and customer experiences across Skill Builder. - Continuously explore and evaluate state-of-the-art techniques and methodologies to improve the accuracy and efficiency of AI/ML systems. - Communicate complex technical concepts effectively to both technical and non-technical stakeholders, providing clear explanations and guidance on proposed solutions and their potential impact. About the team Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon conferences, inspire us to never stop embracing our uniqueness. 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. 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.