How three science PhDs found different career paths at Amazon

Their doctoral degrees help these product managers bridge the gap between business and science.

While most students get into science PhD programs envisioning a career in research, there are many other paths to pursue. At Amazon, employees with advanced degrees in science find roles in product and program management, and other careers that depart from the traditional academic route.

The choice is not as unusual as you might think. Almost 40% of U.S. doctoral scientists and engineers who are employed describe their primary or secondary work activity as “management, sales or administration,” according to the 2017 Survey of Doctorate Recipients conducted by the National Center for Science and Engineering Statistics.

Tingting Sha Irene Song Ahmed El Saadany Amazon Science.jpg
Left to right: Tingting Sha, senior manager; Irene Song, principal product manager; and Ahmed El Saadany, senior product manager; all three are scientists who have migrated to product management roles within Amazon's Supply Chain Optimization Technologies (SCOT) organization. Each says their science credentials help them influence the development of new products and services.

Nor does working in one of those areas mean leaving behind all the training they received while obtaining their advanced degrees.

Individuals who persevere through an arduous PhD program develop the ability to think deeply about problems and develop solutions for them, a skill that is crucial for product managers.

“The mental model and the foundational skill sets are the same,” said Tingting Sha, senior manager at Amazon Supply Chain Optimization Technologies (SCOT). “How do we look at a problem? How do we use a scientific solution to address that problem and better serve our customers? All the learnings I had with my PhD are applicable to answer those questions.”

Sha is not the only scientist turned product manager. We spoke with her, Irene Song, principal product manager, and Ahmed El Saadany, senior product manager, about their science backgrounds and what motivated them to pursue a career in industry.

Literature, finance, advertising: Irene Song’s non-traditional background

As an undergrad at Smith College, Song never contemplated working in the tech industry or even following a science-related career. She wanted to be a writer.

“My plan was to go to grad school and study literature,” she says.

When she finished her bachelor’s degree in literature and math and got a job offer from an investment bank, she decided to work for a couple of years before following her literary path. She ended up enjoying finance and decided to apply for an MS/PhD program in financial engineering at Columbia University. It was 2008, and her manager advised her that it made sense to take a break and go to grad school given the financial crisis.

I always liked observing what people are doing to make business decisions and then figuring out a way to automate that based on data.
Irene Song

When Song finished her PhD, which focused on portfolio optimization, she knew she didn’t want to remain in academia because she didn’t enjoy conducting research in isolation. But she also didn’t want to go back to finance. After attending a talk about how the advertising industry was going digital, she became interested in applying her portfolio optimization experience in advertising.

For three years she worked for an advertising agency technology team, developing a platform to help clients determine how to invest advertising funds in an optimal way. She was responsible for connecting business, science, and technology.

“What I realized through working in different industries is that I always liked observing what people are doing to make business decisions and then figuring out a way to automate that based on data and so we can make decisions more rationally in a scalable manner,” she said.

As she described her interests to a friend who had gone to work for Amazon, he told her that they aligned with the description of a product manager role. She then had a call with an Amazon manager, which turned into a successful job interview. The fact that her team makes business decisions while also owning the technology used to implement scientific solutions made the job a great fit for her, Song said. It also fulfilled her interest of automating solutions at scale.

Today she works across multiple teams to develop solutions for several types of opportunities, serving as a bridge between business, science, and engineering. Recently, for example, she and her team developed a proposal to assess inventory capacity at warehouses during holidays. Taking lessons learned during the 2020 holiday season around capacity and inventory volume, her team is working to adapt in preparation for this year’s holidays.

Ahmed El Saadany moved to industry for “real world” experiences

El Saadany was following a successful academic path in the field of supply chain management. A few of his research papers, which in general looked into how to preserve the environment while also improving the supply chain, got hundreds of citations. One of the projects he worked on during his PhD at Ryerson University in Canada focused on determining effective incentives for customers to return products that they no longer use so they can be sold again or recycled.

Even as a scientist, not just as an engineer, I realized I’d learn more by working in industry, especially when it comes to supply chain
Ahmed El Saadany

At one point in his academic trajectory, his models became very complicated. He felt he was relying on too many assumptions and that it wouldn’t be fruitful to continue producing increasingly complex models without observing how things worked in the “real world”.

“Even as a scientist, not just as an engineer, I realized I’d learn more by working in industry, especially when it comes to supply chain,” he said.

El Saadany joined Amazon in January 2016 after working in consulting for a few years. “One of the things that I found similar between academia and Amazon is that you have the chance and the time to do a really deep dive into one area — to understand all the details about it,” he said.

At Amazon, El Saadany and his team assess situations where, for example, Amazon ends up with more inventory than is needed.

“In these instances, we need to either improve the sales, offer a discount, market it in a different way, or work with the vendor to make sure that we have a very efficient and agile supply chain,” he said. “Because if we keep that product forever in our inventory, it will lose value, and it won’t help our customers. So, the question is, ‘How can we better serve our customers and maximize the value of the product?’”

El Saadany notes that the product manager role is the right fit for researchers who want to build on what they’ve learned as scientists and develop tools that help people directly.

“When you build something within Amazon, you can see the impact of your work as an Amazon delivery arrives on your doorstep,” he said.

Tinting Sha’s trajectory: From designing CPUs to leading a team of 25 people

Like El Saadany, one reason Sha decided to move into industry was that she felt the assumptions made in academia did not always correspond to reality.

“I wanted to understand what it was like to get more realistic, because research might go so off the track when you don't know the business context,” she said.

She also wanted to see her research have real-world impact.

Keep learning and being curious, there’s always going to be a learning process.
Tingting Sha

For her PhD, Sha studied computer architecture at the University of Pennsylvania. Back in college, she was fascinated by how central processing units (CPUs) processed so many different types of information. That’s why going to UPenn — where ENIAC was developed — was a straightforward decision. In her research, she focused on how to store and retrieve data more efficiently.

While her initial plan was to become an academic, her life’s journey took a new path after an internship at Intel.

“Over time, I determined that my true passion is trying to build something that's going to help my target customers,” said Sha. “And in order to do so, I needed to equip myself not only with science and engineering capabilities, but also with the business aspects.”

That's why she obtained a master’s in business administration from the Massachusetts Institute of Technology in 2015, and then joined Amazon.

Although she doesn’t design CPUs anymore, Sha said the problem-solving abilities harnessed during her PhD studies at UPenn are in constant use. Since joining Amazon, she continues to learn new skills required for her senior manager, product manager role.

Her philosophy: “Keep learning and being curious,” she says. “There’s always going to be a learning process.” Right now, as she leads a team of 25 people, she’s focused on growing her skills as a leader.

Impacting science as a product manager

For Song, El Saadany, and Sha, their science credentials help them influence the development of new products and services.

“At Amazon, you end up doing something at the forefront of science, as a lot of what we do is not actually published out there,” El Saadany said. “We're building new things because we're serving customers in ways that have never been done before.”

The reason why scientists feel comfortable writing a science proposal with me is that they know that, when I’m editing it, I understand what’s in the proposal.
Irene Song

“The reason why scientists feel comfortable writing a science proposal with me is that they know that, when I’m editing it, I understand what’s in the proposal,” said Song. “Basically, it reduces the gap of communication between people with different backgrounds.”

One bit of career advice she has for scientists aspiring to a product manager position is to focus on communication skills.

“If you want to be in the product role, more than understanding science, you must be able to communicate what the problem is — and what the solution is — to various audiences, regardless of their backgrounds.”

Sha says SCOT teams are always looking for “Amazonians currently not working at Amazon.” By that she means individuals who have a strong sense of ownership and who make good judgements in both diving deep on a topic, and thinking big.

“You need to both zoom into the details and really understand the problem, while also popping up to see the bigger picture.”

Related content

IN, KA, Bengaluru
Do you want to join an innovative team of scientists who use machine learning and statistical techniques to create state-of-the-art solutions for providing better value to Amazon’s customers? Do you want to build and deploy advanced ML systems that help optimize millions of transactions every day? Are you excited by the prospect of analyzing and modeling terabytes of data to solve real-world problems? Do you like to own end-to-end business problems/metrics and directly impact the profitability of the company? Do you like to innovate and simplify? If yes, then you may be a great fit to join the Machine Learning team for India Consumer Businesses. Machine Learning, Big Data and related quantitative sciences have been strategic to Amazon from the early years. Amazon has been a pioneer in areas such as recommendation engines, ecommerce fraud detection and large-scale optimization of fulfillment center operations. As Amazon has rapidly grown and diversified, the opportunity for applying machine learning has exploded. We have a very broad collection of practical problems where machine learning systems can dramatically improve the customer experience, reduce cost, and drive speed and automation. These include product bundle recommendations for millions of products, safeguarding financial transactions across by building the risk models, improving catalog quality via extracting product attribute values from structured/unstructured data for millions of products, enhancing address quality by powering customer suggestions We are developing state-of-the-art machine learning solutions to accelerate the Amazon India growth story. Amazon India is an exciting place to be at for a machine learning practitioner. We have the eagerness of a fresh startup to absorb machine learning solutions, and the scale of a mature firm to help support their development at the same time. As part of the India Machine Learning team, you will get to work alongside brilliant minds motivated to solve real-world machine learning problems that make a difference to millions of our customers. We encourage thought leadership and blue ocean thinking in ML. Key job responsibilities Use machine learning and analytical techniques to create scalable solutions for business problems Analyze and extract relevant information from large amounts of Amazon’s historical business data to help automate and optimize key processes Design, develop, evaluate and deploy, innovative and highly scalable ML models Work closely with software engineering teams to drive real-time model implementations Work closely with business partners to identify problems and propose machine learning solutions Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model maintenance Work proactively with engineering teams and product managers to evangelize new algorithms and drive the implementation of large-scale complex ML models in production Leading projects and mentoring other scientists, engineers in the use of ML techniques About the team International Machine Learning Team is responsible for building novel ML solutions that attack India first (and other Emerging Markets across MENA and LatAm) problems and impact the bottom-line and top-line of India business. Learn more about our team from https://www.amazon.science/working-at-amazon/how-rajeev-rastogis-machine-learning-team-in-india-develops-innovations-for-customers-worldwide
ES, B, Barcelona
Are you a scientist passionate about advancing the frontiers of computer vision, machine learning, or large language models? Do you want to work on innovative research projects that lead to innovative products and scientific publications? Would you value access to extensive datasets? If you answer yes to any of these questions, you'll find a great fit at Amazon. We're seeking a hands-on researcher eager to derive, implement, and test the next generation of Generative AI, computer vision, ML, and NLP algorithms. Our research is innovative, multidisciplinary, and far-reaching. We aim to define, deploy, and publish pioneering research that pushes the boundaries of what's possible. To achieve our vision, we think big and tackle complex technological challenges at the forefront of our field. Where technology doesn't exist, we create it. Where it does, we adapt it to function at Amazon's scale. We need team members who are passionate, curious, and willing to learn continuously. Key job responsibilities * Derive novel computer vision and ML models or LLMs/VLMs. * Design and develop scalable ML models. * Create and work with large datasets * Work with large GPU clusters. * Work closely with software engineering teams to deploy your innovations. * Publish your work at major conferences/journals. * Mentor team members in the use of your AI models. A day in the life As a Senior Applied Scientist at Amazon, your typical day might look like this: * Dive into coding, deriving new ML models for computer vision or NLP * Experiment with massive datasets on our GPU clusters * Brainstorm with your team to solve complex AI challenges * Collaborate with engineers to turn your research into real products * Write up your findings for publication in top journals or conferences * Mentor junior team members on AI concepts and implementation About the team DiscoVision, a science unit within Amazon's UPMT, focuses on advancing visual content capabilities through state-of-the-art AI technology. Our team specializes in developing state-of-the-art technologies in text-to-image/video Generative AI, 3D modeling, and multimodal Large Language Models (LLMs).
US, WA, Seattle
Are you excited to help customers discover the hottest and best reviewed products? The Discovery Tech team helps customers discover and engage with new, popular and relevant products across Amazon worldwide. We do this by combining technology, science, and innovation to build new customer-facing features and experiences alongside advanced tools for marketers. You will be responsible for creating and building critical services that automatically generate, target, and optimize Amazon’s cross-category marketing and merchandising. Through the enablement of intelligent marketing campaigns that leverage machine-learning models, you will help to deliver the best possible shopping experience for Amazon’s customers all over the globe. We are looking for analytical problem solvers who enjoy diving into data, excited about data science and statistics, can multi-task, and can credibly interface between engineering teams and business stakeholders. Your analytical abilities, business understanding, and technical savvy will be used to identify specific and actionable opportunities to solve existing business problems and look around corners for future opportunities. Your domain spans the design, development, testing, and deployment of data-driven and highly scalable machine learning solutions in product recommendation. As an Applied 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. To know more about Amazon science, please visit https://www.amazon.science
IN, TS, Hyderabad
Do you want to join an innovative team of scientists who leverage machine learning and statistical techniques to revolutionize how businesses discover and purchase products on Amazon? Are you passionate about building intelligent systems that understand and predict complex B2B customer needs? The Amazon Business team is looking for exceptional Applied Science to help shape the future of B2B commerce. Amazon Business is one of Amazon's fastest-growing initiatives focused on serving business customers, from individual professionals to large institutions, with unique and complex purchasing needs. Our customers require sophisticated solutions that go beyond traditional B2C experiences, including bulk purchasing, approval workflows, and business-grade service support. The AB-MSET Applied Science team focuses on building intelligent systems for delivering personalized, contextual service experiences throughout the customer lifecycle. We apply advanced machine learning techniques to develop sophisticated intent detection models for business customer service needs, create intelligent matching algorithms for optimal service routing based on multiple variables including customer value, maturity, effort, and issue complexity, build predictive models to enable proactive service interventions, design recommendation systems for self-service solutions, and develop ML models for automated service resolution. As an Applied Scientist on the team, you will design and develop state-of-the-art ML models for service intent classification, routing optimization, and customer experience personalization. You will analyze large-scale business customer interaction data to identify patterns and opportunities for automation, create scalable solutions for complex B2B service scenarios using advanced ML techniques, and work closely with engineering teams to implement and deploy models in production. You will collaborate with business stakeholders to identify opportunities for ML applications, establish automated processes for model development, validation, and maintenance, lead research initiatives to advance the state-of-the-art in B2B service science, and mentor other scientists and engineers in applying ML techniques to business problems.
US, WA, Seattle
We are seeking a Principal Applied Scientist to lead research and development in automated reasoning, formal verification, and program analysis. You will drive innovation in making formal methods practical and accessible for real-world systems at cloud scale. Key job responsibilities - Lead research initiatives in automated reasoning, formal verification, SMT solving, model checking, or program analysis - Design and implement novel algorithms and techniques that advance the state of the art - Mentor and guide applied scientists, research scientists, and engineers - Collaborate with product teams to transition research into production systems - Define technical vision and strategy for automated reasoning initiatives - Represent AWS in the academic and research community - Drive cross-organizational impact through technical leadership About the team The Automated Reasoning Group at AWS develops and applies cutting-edge formal methods and automated reasoning techniques to ensure the security, reliability, and correctness of AWS services and customer applications. Our work innovates tools and services to perform verification at scale and apply them to build safe and secure systems at AWS. We are also pioneering the use of formal verification and automated reasoning to develop agentic systems, ensuring AI agents operate within defined safety boundaries.
US, WA, Bellevue
As an Applied Scientist on our Central Learning Solutions Team, you will play a critical role in driving the design, development, and delivery of learning programs and initiatives aimed at enhancing leadership and associate development within the organization. You will leverage your expertise in learning science, data analysis, and statistical model design to create impactful learning journey roadmap that align with organizational goals and priorities. Key job responsibilities Research and Analysis: - Conduct research on learning and development trends, theories, and best practices related to leadership and associate development - Analyze data to identify learning needs, performance gaps, and opportunities for improvement within the organization. - Use data-driven insights to inform the design and implementation of learning interventions. Program Design and Development: - Collaborate with cross-functional teams to develop comprehensive learning programs focused on leadership development and associate growth - Design learning experiences using evidence-based instructional strategies, adult learning principles, and innovative technologies. - Create engaging and interactive learning materials, including e-learning modules, instructor-led workshops, and multimedia resources. Evaluation and Continuous Improvement: - Develop evaluation frameworks to assess the effectiveness and impact of learning programs on leadership development and associate performance - Collect and analyze feedback from participants and stakeholders to identify strengths, areas for improvement, and future learning needs. - Iterate on learning interventions based on evaluation results and feedback to continuously improve program outcomes Thought Leadership and Collaboration: - Serve as a subject matter expert on learning science, instructional design, and leadership development within the organization - Collaborate with stakeholders across the company to align learning initiatives with strategic priorities and business objectives - Share knowledge and best practices with colleagues to foster a culture of continuous learning and development.
US, WA, Bellevue
Amazon Leo is an initiative to increase global broadband access through a constellation of 3,236 satellites in low Earth orbit (LEO). Its mission is to bring fast, affordable broadband to unserved and underserved communities around the world. Amazon Leo will help close the digital divide by delivering fast, affordable broadband to a wide range of customers, including consumers, businesses, government agencies, and other organizations operating in places without reliable connectivity. Do you get excited by aerospace, space exploration, and/or satellites? Do you want to help build solutions at Amazon Leo to transform the space industry? If so, then we would love to talk! Key job responsibilities Work cross-functionally with product, business development, and various technical teams (engineering, science, simulations, etc.) to execute on the long-term vision, strategy, and architecture for the science-based global demand forecast. Design and deliver modern, flexible, scalable solutions to integrate data from a variety of sources and systems (both internal and external) and develop Bandwidth Usage models at granular temporal and geographic grains, deployable to Leo traffic management systems. Work closely with the capacity planning science team to ensure that demand forecasts feed seamlessly into their systems to deliver continuous optimization of resources. Lead short and long terms technical roadmap definition efforts to deliver solutions that meet business needs in pre-launch, early-launch, and mature business phases. Synthesize and communicate insights and recommendations to audiences of varying levels of technical sophistication to drive change across Amazon Leo. 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. About the team The Amazon Leo Global Demand Planning team's mission is to map customer demand across space and time. We enable Amazon Leo's long-term success by delivering actionable insights and scientific forecasts across geographies and customer segments to empower long range planning, capacity simulations, business strategy, and hardware manufacturing recommendations through scalable tools and durable mechanisms.
US, CA, Pasadena
Do you enjoy solving challenging problems and driving innovations in research? As a Research Science intern with the Quantum Algorithms Team at CQC, you will work alongside global experts to develop novel quantum algorithms, evaluate prospective applications of fault-tolerant quantum computers, and strengthen the long-term value proposition of quantum computing. A strong candidate will have experience applying methods of mathematical and numerical analysis to assess the performance of quantum algorithms and establish their advantage over classical algorithms. Key job responsibilities We are particularly interested in candidates with expertise in any of the following subareas related to quantum algorithms: quantum chemistry, many-body physics, quantum machine learning, cryptography, optimization theory, quantum complexity theory, quantum error correction & fault tolerance, quantum sensing, and scientific computing, among others. A day in the life Throughout your journey, you'll have access to unparalleled resources, including state-of-the-art computing infrastructure, cutting-edge research papers, and mentorship from industry luminaries. This immersive experience will not only sharpen your technical skills but also cultivate your ability to think critically, communicate effectively, and thrive in a fast-paced, innovative environment where bold ideas are celebrated. 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. Hybrid Work We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our U.S. Amazon offices. This is not a remote internship opportunity. About the team Amazon Web Services (AWS) Center for Quantum Computing (CQC) is a multi-disciplinary team of theoretical and experimental physicists, materials scientists, and hardware and software engineers on a mission to develop a fault-tolerant quantum computer.
US, CA, Pasadena
We’re on the lookout for the curious, those who think big and want to define the world of tomorrow. At Amazon, you will grow into the high impact, visionary person you know you’re ready to be. Every day will be filled with exciting new challenges, developing new skills, and achieving personal growth. How often can you say that your work changes the world? At Amazon, you’ll say it often. Join us and define tomorrow. The Amazon Web Services (AWS) Center for Quantum Computing (CQC) in Pasadena, CA, is looking for a Quantum Research Scientist Intern in the Device and Architecture Theory group. You will be joining a multi-disciplinary team of scientists, engineers, and technicians, all working at the forefront of quantum computing to innovate for the benefit of our customers. Key job responsibilities As an intern with the Device and Architecture Theory team, you will conduct pathfinding theoretical research to inform the development of next-generation quantum processors. Potential focus areas include device physics of superconducting circuits, novel qubits and gate schemes, and physical implementations of error-correcting codes. You will work closely with both theorists and experimentalists to explore these directions. We are looking for candidates with excellent problem-solving and communication skills who are eager to work collaboratively in a team environment. 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 quantum computing 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. A day in the life 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. AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS. Within AWS UC, Amazon Dedicated Cloud (ADC) roles engage with AWS customers who require specialized security solutions for their cloud services. 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. 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. 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.
US, MA, N.reading
Amazon Industrial Robotics is seeking exceptional talent to help develop the next generation of advanced robotics systems that will transform automation at Amazon's scale. We're building revolutionary robotic systems that combine cutting-edge AI, sophisticated control systems, and advanced mechanical design to create adaptable automation solutions capable of working safely alongside humans in dynamic environments. This is a unique opportunity to shape the future of robotics and automation at an unprecedented scale, working with world-class teams pushing the boundaries of what's possible in robotic dexterous manipulation, locomotion, and human-robot interaction. We are seeking a talented Applied Scientist to join our advanced robotics team, focusing on developing and applying cutting-edge simulation methodologies for advanced robotics systems. This role centers on research and development of physics-based simulation techniques, sim-to-real transfer methods, and machine learning approaches that enable rapid development, testing, and validation of robotic systems operating in complex, real-world environments. Key job responsibilities - Advance physics-based simulation fidelity for contact-rich manipulation and locomotion - Design and build high-performance simulation tools integrated into a production robotics stack - Translate research ideas into robust, scalable software pipelines - Develop methods to quantify and reduce simulation-to-reality gaps across design, safety, and control - Architect scalable simulation solutions for rigid and deformable body dynamics - Build simulation pipelines optimized for large-scale reinforcement and policy learning - Establish frameworks for continuous simulation improvement using real-world deployment data - Collaborate with engineering, science, and safety teams on simulation requirements and validation About the team Our team is building a comprehensive simulation platform for advanced robotics development, combining locomotion and manipulation capabilities. We operate at the cutting edge of physics simulation, reinforcement learning, and sim-to-real transfer, collaborating with world-class robotics engineers, applied scientists, and mechanical designers in a fast-paced, innovation-driven environment. This role uniquely combines fundamental research with real-world deployment. You will pursue core research questions in physics-based simulation while seeing your work translated into production systems, validated on real hardware, and informed by deployment data. Working alongside Simulation Software Engineers, you will help transform research ideas into scalable, production-grade simulation capabilities that directly impact how robots are designed, trained, and deployed.