Mahdieh Allahviranloo, an Amazon Visiting Academic, is seen standing in the back of an Amazon delivery vehicle. The truck is empty, it's back door is open, and Mahdieh is smiling while wearing a safety vest.
Mahdieh Allahviranloo, an Amazon Visiting Academic with the Last Mile Science team, is spending her sabbatical from the City College of New York researching ways to boost efficiency in Amazon's last-mile delivery network.

Where machine learning models meet mobility and human behavior

Mahdieh Allahviranloo is using her expertise in transportation engineering to assist last-mile delivery operations at Amazon.

On a recent ride-along with an Amazon delivery driver in New York City, Mahdieh Allahviranloo got a firsthand look at the gap between algorithm logic and city logic. The driver’s intelligence was overriding the forecasting machine’s intelligence.

Why? Because the driver knew the challenges of street parking in Brooklyn, among other nuances of city deliveries, and she was aggregating packages to deliver on foot from fewer vehicle stops.

"The driver was so fast and very skilled. She was doing a lot of smart optimization on her own," Allahviranloo recalls.

As a Visiting Academic with the Amazon Last Mile Science team, Allahviranloo explores this space between computational science and human intuition. She is spending her sabbatical from the City College of New York (CCNY-CUNY), where she is an associate professor of civil engineering, researching ways to boost efficiency in Amazon's last-mile delivery network.

Maximum utility, minimum cost

She took the observational ride in Brooklyn to contribute to the work of her colleagues in Seattle-based Amazon last mile transportation team. Most of Allahviranloo's time at Amazon, which began in September 2021, has focused on optimizing last-mile operations. This includes the operation from delivery stations, which are the last stop for packages before they’re loaded up for the trip to customers.

Operations research
How Customer Order and Network Density OptimizeR (CONDOR) has led to improved delivery routes.

In her research, Allahviranloo integrates data mining, statistical analysis, and optimization models to study how individuals move in urban areas. Among many other publications, she has published papers on the daily activity patterns of travelers, peer-to-peer crowdshipping, vehicle routing and resource allocation problems, smart cities, and self-driving vehicles.

At Amazon, she is applying her expertise to the challenges of managing shipping volume and labor across delivery stations. Though the context is a departure from her focus on urban transportation, there are many similarities, since both are heavily using concepts of network modeling and machine learning.

"They're all mathematical problems," Allahviranloo says. "We are solving network models to gain the maximum utility at the minimum cost."

In one project, she is applying a method called consensus planning to Amazon's network of delivery stations. The model attempts to create consensus among different "agents," or entities within a network, to pinpoint and prevent potential bottlenecks. In the context of delivery stations, the agents might be delivery service providers, delivery station labor planning teams, and the physical capacity of the station in terms of conveyor belts, space, and so on. Any misalignment in planning among these different operational groups would have significant impacts.

Allahviranloo's model examines how to plan for shipping volume in two hierarchies: one, by planning for labor and capacity within each delivery station, and two, by designing a communication system across hundreds of delivery stations so that stations can absorb overflow from one another when needed.

The project is an extension of similar work across fulfillment centers done by Amazon's Supply Chain Optimization Technologies team. The overarching goal for the work is to deliver packages as efficiently as possible to customers at the least cost.

Last-mile challenges
INFORMS talk explores techniques Amazon’s Supply Chain Optimization Technologies organization is testing to fulfill customer orders more efficiently.

Other projects which she is directly involved fall under the umbrella of picklist optimization modeling, aiming to incorporate an idea of package size, weight, and location to design better pick lists, which tell delivery station item staff which items need to be retrieved from racks for staging and loading.

"We are looking at how we can assign tasks optimally so that everyone finishes around the same time and there is a balanced allocation of tasks among associates," Allahviranloo says.

Having a voice and using it to support others

Allahviranloo has long been interested in the variables that go into mobility of all kinds. She became interested in the field through two undergraduate classes at Sharif University of Technology in Tehran: transportation systems and engineering economics.

Mahdieh Allahviranloo is seen outside on a boat wearing a white shirt that has sunglasses clipped to it, she is sitting and looking to her left
Mahdieh Allahviranloo says transportation fascinated her as a research topic because it combined problems of econometrics and optimization with a wild card: people.

“I realized I liked applying decision-making processes and mathematical modeling in innovative ways to solve different engineering problems,” she says.

After getting her civil engineering degree in Iran, she got her PhD in transportation engineering at the University of California, Irvine. Transportation fascinated Allahviranloo because it combined problems of econometrics and optimization with a wild card: people.

"Human behavior is totally uncertain, which makes transportation problems very complex to design and to think about," she says.

After learning about Amazon's Visiting Academic program, Allahviranloo began working with Amazon part-time last year and is now full time through August 2023.

“The Visiting Academic program is a win-win for researchers and Amazon, as it allows Amazon to tap into top scientific talent and enables those researchers to work on large and complex real-world problems,” said Julian Pachon, worldwide director of Last Mile Science and Analytics.

Allahviranloo says she enjoys working with a team where she learns from others, but people are open to new approaches.

Related content
Dartmouth College professor is focusing on broader educational efforts with customers and other stakeholders.

"New ideas are not dismissed. We talk, we negotiate, and this provides a very safe environment where ideas are exchanged, and I’m able to have my voice," she said. "I’m not scared of being challenged, but at the same time, I receive constructive critiques from my colleagues, which is amazing."

Allahviranloo also volunteers as a mentor with the CCNY Women's Robotics Club, advising students from disciplines such as mechanical engineering, electrical engineering, and computer science as they pursue robotics projects.

"The main purpose is to give young women the courage to get into programming and have hands-on experience," she says. "I believe that society is successful when everybody's on the same level. If you sit on a chair and one of the legs is short, you're going to fall down."

For aspiring engineers, Allahviranloo recommends being guided by your passion and the process rather than having a goal, since goals can change.

"The main thing is to know what drives you and what makes you happy," she says. "Once you're happy, work is not going to look like work. It's going to be a very joyful process that you have a passion for."

It's the kind of joy Allahviranloo is finding while solving problems on the streets of New York City and on the floors of Amazon’s delivery stations.

Related content

US, WA, Seattle
The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through novel 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 ecosystem. 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. Key job responsibilities As an applied scientist on our team, you will * Develop AI solutions for Sponsored Brands advertiser and shopper experiences. Build recommendation systems that leverage generative models to develop and improve campaigns. * You invent and design new solutions for scientifically-complex problem areas and/or opportunities in new business initiatives. * You drive or heavily influence the design of scientifically-complex software solutions or systems, for which you personally write significant parts of the critical scientific novelty. You take ownership of these components, providing a system-wide view and design guidance. These systems or solutions can be brand new or evolve from existing ones. * Define a long-term science vision and roadmap for our Sponsored Brands advertising business, driven from our customers' needs, translating that direction into specific plans for applied scientists and engineering teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding. * Work closely with engineers and product managers to design, implement and launch AI solutions end-to-end; * Design and conduct A/B experiments to evaluate proposed solutions based on in-depth data analyses; * Think big about the arc of development of Gen AI over a multi-year horizon, and identify new opportunities to apply these technologies to solve real-world problems * Effectively communicate technical and non-technical ideas with teammates and stakeholders; * Translate complex scientific challenges into clear and impactful solutions for business stakeholders. * Mentor and guide junior scientists, fostering a collaborative and high-performing team culture. * Stay up-to-date with advancements and the latest modeling techniques in the field About the team The Sponsored Brands Impressions-based Offerings team is responsible for evolving the value proposition of Sponsored Brands to drive brand advertising in retail media at scale, helping brands get discovered, acquire new customers and sustainably grow customer lifetime value. We build end-to-end solutions that enable brands to drive discovery, visibility and share of voice. This includes building advertiser controls, shopper experiences, monetization strategies and optimization features. We succeed when (1) shoppers discover, engage and build affinity with brands and (2) brands can grow their business at scale with our advertising products. #GenAI
US, CA, San Diego
The Private Brands team is looking for a Sr. Research Scientist to join the team in building science solutions at scale. Our team applies Optimization, Machine Learning, Statistics, Causal Inference, and Econometrics/Economics to derive actionable insights about the complex economy of Amazon’s retail business and develop Statistical Models and Algorithms to drive strategic business decisions and improve operations. We are an interdisciplinary team of Scientists, Engineers, PMTs and Economists. Key job responsibilities You will work with business leaders, scientists, and economists to translate business and functional requirements into concrete deliverables, including the design, development, testing, and deployment of highly scalable optimization solutions and ML models. This is a unique, high visibility opportunity for someone who wants to have business impact, dive deep into large-scale problems, enable measurable actions on the consumer economy, and work closely with scientists and economists. As a Sr Scientist, you bring business and industry context to science and technology decisions. You set the standard for scientific excellence and make decisions that affect the way we build and integrate algorithms. Your solutions are exemplary in terms of algorithm design, clarity, model structure, efficiency, and extensibility. You tackle intrinsically hard problems, acquiring expertise as needed. You decompose complex problems into straightforward solutions. We are particularly interested in candidates with experience in Operations Research, ML and predictive models and working with distributed systems. Academic and/or practical background in Operations Research and Machine Learning specifically Reinforcement Learning are particularly relevant for this position. To know more about Amazon science, Please visit https://www.amazon.science About the team We are a one pizza, agile team of scientists focused on solving supply chain challenges for Amazon Private Brands products. We collaborate with Amazon central teams like SCOT and develop both central as well as APB-specific solutions to address various challenges, including sourcing, demand forecasting, ordering optimization, inventory distribution, and inventory health management. Working closely with business stakeholders, Product Management Teams (PMTs), and engineering partners, we drive projects from initial concept through production deployment and ongoing monitoring.
US, CA, Sunnyvale
As a Reinforcement Learning Controls Scientist, you will be responsible for developing Reinforcement Learning models to control complex electromechanical systems. You will take responsibility for defining frameworks, performing analysis, and training models that guide and inform mechanical and electrical designs, software implementation, and other software modules that affect overall device safety and performance. You understand trade-offs between model-based and model-free approaches. You will demonstrate cross-functional collaboration and influence to accomplish your goals. You will play a role in defining processes and methods to improve the productivity of the entire team. You will interface with Amazon teams outside your immediate organization to collaborate and share knowledge. You will investigate applicable academic and industry research, prototype and test solutions to support product features, and design and validate production designs that deliver an exceptional user experience. Key job responsibilities - Produce models and simulations of complex, high degree-of-freedom dynamic electromechanical systems - Train Reinforcement Learning control policies that achieve performance targets within hardware and software constraints - Hands-on prototyping and testing of physical systems in the lab - Influence hardware and software design decisions owned by other teams to optimize system-level performance - Work with cross-functional teams (controls, firmware, perception, planning, sensors, mechanical, electrical, etc.) to solve complex system integration issues - Define key performance indicators and allocate error budgets across hardware and software modules - Perform root cause analysis of system-level failures and distinguish between hardware/software failures and hardware/software mitigations - Translate business requirements to engineering requirements and identify trade-offs and sensitivities - Mentor junior engineers in good design practice; actively participate in hiring of new team members About the team The Dynamic Systems and Control team develops models, algorithms, and code to bridge hardware and software development teams and bring robotic products to life. We contributed to Amazon Astro (https://www.amazon.com/Introducing-Amazon-Astro/dp/B078NSDFSB) and Echo Show 10 (https://www.amazon.com/echo-show-10/dp/B07VHZ41L8/), along with several new technology introductions and unannounced products currently in development.
US, WA, Seattle
About Sponsored Products and Brands: The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through industry leading 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. About Our Team: The Sponsored Brands Impressions-based Offerings team is responsible for evolving the value proposition of Sponsored Brands to drive brand advertising in retail media at scale, helping brands get discovered, acquire new customers and sustainably grow customer lifetime value. We build end-to-end solutions that enable brands to drive discovery, visibility and share of voice. This includes building advertiser controls, shopper experiences, monetization strategies and optimization features. We succeed when (1) shoppers discover, engage and build affinity with brands and (2) brands can grow their business at scale with our advertising products. About This Role: As a Principal Scientist for the team, you will have the opportunity to apply your deep subject matter expertise in the area of ML, LLM and GenAI models. You will invent new product experiences that enable novel advertiser and shopper experiences. This role will liaise with internal Amazon partners and work on bringing state-of-the-art GenAI models to production, and stay abreast of the latest developments in the space of GenAI and identify opportunities to improve the efficiency and productivity of the team. Additionally, you will define a long-term science vision for our advertising business, driven by our customer’s needs, and translate it into actionable plans for our team of applied scientists and engineers. This role will play a critical role in elevating the team’s scientific and technical rigor, identifying and implementing best-in-class algorithms, methodologies, and infrastructure that enable rapid experimentation and scaling. You will communicate learnings to leadership and mentor and grow Applied AI talent across org. * Develop AI solutions for Sponsored Brands advertiser and shopper experiences. Build monetization and optimization systems that leverage generative models to value and improve campaign performance. * Define a long-term science vision and roadmap for our Sponsored Brands advertising business, driven from our customers' needs, translating that direction into specific plans for applied scientists and engineering teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding. * Design and conduct A/B experiments to evaluate proposed solutions based on in-depth data analyses. * Effectively communicate technical and non-technical ideas with teammates and stakeholders. * Stay up-to-date with advancements and the latest modeling techniques in the field. * Think big about the arc of development of Gen AI over a multi-year horizon and identify new opportunities to apply these technologies to solve real-world problems. #GenAI
US, WA, Seattle
Innovators wanted! Are you an entrepreneur? A builder? A dreamer? This role is part of an Amazon Special Projects team that takes the company’s Think Big leadership principle to the limits. If you’re interested in innovating at scale to address big challenges in the world, this is the team for you. As a Data Scientist on our team, you'll analyze complex data, develop statistical methodologies, and provide critical insights that shape how we optimize our solutions. Working closely with our Applied Science team, you'll help build robust analytical frameworks to improve healthcare outcomes. This role offers a unique opportunity to impact healthcare through data-driven innovation. Key job responsibilities In this role, you will: - Analyze complex healthcare data to identify patterns, trends, and insights - Develop and validate statistical methodologies - Create and maintain analytical frameworks - Provide recommendations on data collection strategies - Collaborate with Applied Scientists to support model development efforts - Design and implement statistical analyses to validate analytical approaches - Present findings to stakeholders and contribute to scientific publications - Work with cross-functional teams to ensure solutions are built on sound statistical foundations - Design and implement causal inference analyses to understand underlying mechanisms - Develop frameworks for identifying and validating causal relationships in complex systems - Work with stakeholders to translate causal insights into actionable recommendations A day in the life You'll work with large-scale healthcare datasets, conducting sophisticated statistical analyses to generate actionable insights. You'll collaborate with Applied Scientists to validate model predictions and ensure statistical rigor in our approach. Regular interaction with product teams will help translate analytical findings into practical improvements for our services. About the team We represent Amazon's ambitious vision to solve the world's most pressing challenges. We are exploring new approaches to enhance research practices in the healthcare space, leveraging Amazon's scale and technological expertise. We operate with the agility of a startup while backed by Amazon's resources and operational excellence. We're looking for builders who are excited about working on ambitious, undefined problems and are comfortable with ambiguity.
US, WA, Seattle
Innovators wanted! Are you an entrepreneur? A builder? A dreamer? This role is part of an Amazon Special Projects team that takes the company’s Think Big leadership principle to the limits. If you’re interested in innovating at scale to address big challenges in the world, this is the team for you. As an Applied Scientist on our team, you will focus on building state-of-the-art ML models for healthcare. Our team rewards curiosity while maintaining a laser-focus in bringing products to market. Competitive candidates are responsive, flexible, and able to succeed within an open, collaborative, entrepreneurial, startup-like environment. At the forefront of both academic and applied research in this product area, you have the opportunity to work together with a diverse and talented team of scientists, engineers, and product managers and collaborate with other teams. This role offers a unique opportunity to work on projects that could fundamentally transform healthcare outcomes. Key job responsibilities In this role, you will: • Design and implement novel AI/ML solutions for complex healthcare challenges • Drive advancements in machine learning and data science • Balance theoretical knowledge with practical implementation • Work closely with customers and partners to understand their requirements • 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 • Establish best practices for ML experimentation, evaluation, development and deployment • Partner with leadership to define roadmap and strategic initiatives 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 You will solve real-world problems by getting and analyzing large amounts of data, generate insights and opportunities, design simulations and experiments, and develop statistical and ML models. The team is driven by business needs, which requires collaboration with other Scientists, Engineers, and Product Managers across the Special Projects organization. You will prepare written and verbal presentations to share insights to audiences of varying levels of technical sophistication. About the team We represent Amazon's ambitious vision to solve the world's most pressing challenges. We are exploring new approaches to enhance research practices in the healthcare space, leveraging Amazon's scale and technological expertise. We operate with the agility of a startup while backed by Amazon's resources and operational excellence. We're looking for builders who are excited about working on ambitious, undefined problems and are comfortable with ambiguity.
US, WA, Seattle
Innovators wanted! Are you an entrepreneur? A builder? A dreamer? This role is part of an Amazon Special Projects team that takes the company’s Think Big leadership principle to the limits. If you’re interested in innovating at scale to address big challenges in the world, this is the team for you. As an Applied Scientist on our team, you will focus on building state-of-the-art ML models for healthcare. Our team rewards curiosity while maintaining a laser-focus in bringing products to market. Competitive candidates are responsive, flexible, and able to succeed within an open, collaborative, entrepreneurial, startup-like environment. At the forefront of both academic and applied research in this product area, you have the opportunity to work together with a diverse and talented team of scientists, engineers, and product managers and collaborate with other teams. This role offers a unique opportunity to work on projects that could fundamentally transform healthcare outcomes. Key job responsibilities In this role, you will: • Design and implement novel AI/ML solutions for complex healthcare challenges • Drive advancements in machine learning and data science • Balance theoretical knowledge with practical implementation • Work closely with customers and partners to understand their requirements • 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 • Establish best practices for ML experimentation, evaluation, development and deployment • Partner with leadership to define roadmap and strategic initiatives 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 You will solve real-world problems by getting and analyzing large amounts of data, generate insights and opportunities, design simulations and experiments, and develop statistical and ML models. The team is driven by business needs, which requires collaboration with other Scientists, Engineers, and Product Managers across the Special Projects organization. You will prepare written and verbal presentations to share insights to audiences of varying levels of technical sophistication. About the team We represent Amazon's ambitious vision to solve the world's most pressing challenges. We are exploring new approaches to enhance research practices in the healthcare space, leveraging Amazon's scale and technological expertise. We operate with the agility of a startup while backed by Amazon's resources and operational excellence. We're looking for builders who are excited about working on ambitious, undefined problems and are comfortable with ambiguity.
US, WA, Seattle
Innovators wanted! Are you an entrepreneur? A builder? A dreamer? This role is part of an Amazon Special Projects team that takes the company’s Think Big leadership principle to the limits. If you’re interested in innovating at scale to address big challenges in the world, this is the team for you. As an Applied Scientist on our team, you will focus on building state-of-the-art ML models for healthcare. Our team rewards curiosity while maintaining a laser-focus in bringing products to market. Competitive candidates are responsive, flexible, and able to succeed within an open, collaborative, entrepreneurial, startup-like environment. At the forefront of both academic and applied research in this product area, you have the opportunity to work together with a diverse and talented team of scientists, engineers, and product managers and collaborate with other teams. This role offers a unique opportunity to work on projects that could fundamentally transform healthcare outcomes. Key job responsibilities In this role, you will: • Design and implement novel AI/ML solutions for complex healthcare challenges • Drive advancements in machine learning and data science • Balance theoretical knowledge with practical implementation • Work closely with customers and partners to understand their requirements • 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 • Establish best practices for ML experimentation, evaluation, development and deployment • Partner with leadership to define roadmap and strategic initiatives 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 You will solve real-world problems by getting and analyzing large amounts of data, generate insights and opportunities, design simulations and experiments, and develop statistical and ML models. The team is driven by business needs, which requires collaboration with other Scientists, Engineers, and Product Managers across the Special Projects organization. You will prepare written and verbal presentations to share insights to audiences of varying levels of technical sophistication. About the team We represent Amazon's ambitious vision to solve the world's most pressing challenges. We are exploring new approaches to enhance research practices in the healthcare space, leveraging Amazon's scale and technological expertise. We operate with the agility of a startup while backed by Amazon's resources and operational excellence. We're looking for builders who are excited about working on ambitious, undefined problems and are comfortable with ambiguity.
US, WA, Seattle
Innovators wanted! Are you an entrepreneur? A builder? A dreamer? This role is part of an Amazon Special Projects team that takes the company’s Think Big leadership principle to the limits. If you’re interested in innovating at scale to address big challenges in the world, this is the team for you. As a Senior Applied Scientist on our team, you will focus on building state-of-the-art ML models for healthcare. Our team rewards curiosity while maintaining a laser-focus in bringing products to market. Competitive candidates are responsive, flexible, and able to succeed within an open, collaborative, entrepreneurial, startup-like environment. At the forefront of both academic and applied research in this product area, you have the opportunity to work together with a diverse and talented team of scientists, engineers, and product managers and collaborate with other teams. This role offers a unique opportunity to work on projects that could fundamentally transform healthcare outcomes. Key job responsibilities In this role, you will: • Design and implement novel AI/ML solutions for complex healthcare challenges • Drive advancements in machine learning and data science • Balance theoretical knowledge with practical implementation • Work closely with customers and partners to understand their requirements • 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 • Establish best practices for ML experimentation, evaluation, development and deployment • Partner with leadership to define roadmap and strategic initiatives 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 You will solve real-world problems by getting and analyzing large amounts of data, generate insights and opportunities, design simulations and experiments, and develop statistical and ML models. The team is driven by business needs, which requires collaboration with other Scientists, Engineers, and Product Managers across the Special Projects organization. You will prepare written and verbal presentations to share insights to audiences of varying levels of technical sophistication. About the team We represent Amazon's ambitious vision to solve the world's most pressing challenges. We are exploring new approaches to enhance research practices in the healthcare space, leveraging Amazon's scale and technological expertise. We operate with the agility of a startup while backed by Amazon's resources and operational excellence. We're looking for builders who are excited about working on ambitious, undefined problems and are comfortable with ambiguity.
US, MA, Boston
The Artificial General Intelligence (AGI) team is looking for a highly skilled and experienced Sr. Applied Scientist, to support the development and implementation of state-of-the-art algorithms and models for supervised fine-tuning and reinforcement learning through human feedback and complex reasoning; with a focus across text, image, and video modalities. As an Sr. Applied Scientist, you will play a critical role in supporting the development of Generative AI (Gen AI) technologies that can handle Amazon-scale use cases and have a significant impact on our customers' experiences. Key job responsibilities Collaborate with cross-functional teams of engineers, product managers, and scientists to identify and solve complex problems in Gen AI Design and execute experiments to evaluate the performance of different algorithms (PT, SFT, RL) and models, and iterate quickly to improve results Think big about the arc of development of Gen AI over a multi-year horizon, and identify new opportunities to apply these technologies to solve real-world problems Communicate results and insights to both technical and non-technical audiences, including through presentations and written reports About the team We are passionate scientists dedicated to pushing the boundaries of innovation in Gen AI with focus on Software Development use cases.