George Boateng is seen sitting on a chair on a stage while speaking on a panel about his SuaCode work at the African Union’s  2019 Innovating Education in Africa Expo in Gaborone, Botswana.
George Boateng speaking on a panel about his SuaCode work at the African Union’s 2019 Innovating Education in Africa Expo in Gaborone, Botswana.
Helge Tollefsen/African Union

"An accidental project born out of our need to innovate”

Former Amazon intern George Boateng is using machine learning and mobile tech to bridge Africa’s digital divide.

Throughout his short but impressive journey as an engineer and social entrepreneur, George Boateng has seen solutions in scenarios where many people see problems.

While attending boarding school in his home country of Ghana, his fellow students’ clothes were continuously stolen while hanging up to dry. In response, he developed a portable electric dryer.

“I've always really been interested in science, technology, and engineering, and in building things,” said Boateng, 29. “When I was a young boy, my family would travel to visit my grandmother. I was fascinated by her encyclopedias, which she let me take with me so I could do science experiments at home.”

At Dartmouth College, where Boateng earned a bachelor’s degree in computer science, a master’s in computer engineering, and was an E.E. Just STEM Scholar and E.E. Just Graduate Fellow, he teamed up with friends to create the Nsesa Foundation, a nonprofit committed to democratizing STEM education across sub-Saharan Africa. Nsesa teaches young people engineering and computer programming skills to help close STEM education and employment gaps in a place where, according to the World Economic Forum, less than 1% of children finish school with basic coding skills.

George Boateng talks Suacode.ai at the 2020 Africa Summit at Princeton

“My cofounders and I started Nsesa to take Dartmouth’s popular introductory engineering course back home to Ghana,” Boateng explained. “I was amazed by how students, most of whom had not taken any advanced engineering courses, could go through a design and innovation process and actually build solutions to real-life problems and start companies.”

In 2013, he created a modified version of the course called Project iSWEST, a three-week innovation bootcamp in which high school and university students in Ghana could learn coding and innovation skills. When the program’s donated laptop computers had all broken down four years later, Boateng and his colleagues redesigned the eight-week, Java-based training program for devices all of the participants had: smartphones.

“SuaCode was truly an accidental project born out of our need to innovate around a lack of laptops,” said Boateng. That accidental project led MIT Technology Review to recently name Boateng one of its “35 Innovators Under 35.”

SuaCode teaches young students in Africa to code using Android devices and a bilingual (English and French) AI-powered teaching assistant, Kwame, named after Ghana’s first president, Kwame Nkrumah. After four successful pilots between 2018 and 2020, Boateng and his co-founder launched a startup, SuaCode.ai, to turn the program into a mobile app for greater scale and impact.

To date, SuaCode has introduced more than 2,000 learners from 42 African countries to the fundamentals of software. Boateng and his team are currently developing additional courses and partnering with universities across Africa to host and deliver programming through the SuaCode platform.

Related content
Scientists discuss the challenges in developing a system that can accurately estimate body fat percentage and create personalized 3D avatars of users from smartphone photos.

Boateng’s thirst for problem-solving also attracted him to an Alexa AI internship opportunity he saw online in 2020. “The Amazon Halo Band had just been released,” Boateng said. Amazon Halo is a health and wellness membership that integrates with a Halo device to help users manage their overall health. His research focused on Halo Tone, which analyzes qualities of voice, such as energy and positivity, to help members become more aware of how they may sound to others.

“The opportunity to work with the team of applied scientists that developed this first-of-its-kind technology was exciting to me,” he said.

For four months in 2021, Boateng worked with the Cambridge, Mass.-based Alexa AI team on one of the most challenging tasks in computational linguistics — sarcasm detection — with a focus on conversational speech. “Sarcasm can be ambiguous both to humans and to machines,” said Boateng, who completed the internship remotely from Zurich, where he is a doctoral candidate at ETH Zurich. “For example, if someone says ‘I love being ignored’, an emotion recognition system might think the statement is positive because of the use of ‘love’. But once you recognize sarcasm, you can infer this is actually a negative statement.”

Related content
Scientists updated the system to accurately measure body fat percentage and create personalized 3D models even if there’s not enough room to take a full-body photo.

The team took an experimental approach to sarcasm detection with the goal of improving Amazon Halo Tone features, conducting text and speech analyses on hundreds of episodes of two popular TV sitcoms — “Friends” and “The Big Bang Theory”.

“Before diving into this machine learning problem, our first step was to correctly define sarcasm,” Boateng said. “Our approach was grounded in linguistics theory and an empirical understanding of sarcastic utterances to comprehensively address sarcasm detection in conversational speech.”

Boateng and his colleagues developed a taxonomy of incongruity and expression in sarcastic utterances and performed systematic error analysis towards the goal of sarcasm detection. A paper is currently in the works. “We didn’t completely solve sarcasm detection,” Boateng wrote on LinkedIn. “But we have taken a giant step towards that goal.”

George Boateng presenting his PhD research at the second Black in AI workshop at NeurIPS 2018 in Montréal, Canada
George Boateng presenting his PhD research at the second Black in AI workshop at NeurIPS 2018 in Montréal, Canada.
George Boateng

During the internship, Boateng sat in on weekly team meetings and welcomed feedback on his writing and problem-solving approaches from senior scientists. “It was really a big learning experience to understand Amazon’s ‘bias for action’ and ‘customer obsession’ principles,” he said. “I learned that you can’t spend too much time thinking about ways to approach a problem, you have to experiment and deliver results.”

“Alexa attracts top talent in machine learning and speech, due to opportunity to work on cutting-edge applied research,” said Viktor Rozgic, an Alexa principal applied scientist who was Boateng’s manager. “George’s background in developing emotion detection solutions for mobile and data collection design, as well as his ability to handle ambiguity, were very valuable on the project. We were impressed by his versatility, in particular his previous experience working on emotion recognition, mobile applications, and designing data collections.”

Boateng recommends an Amazon science internship for students motivated to tackle “real-world” problems without shying away from uncertainty.

“That’s what really drew me to Amazon,” he said. “A lot of times if you come from a technical background, your focus tends to be theoretical, publishing papers and presenting at conferences. But at Amazon, even though the work is technically rigorous, it’s always linked to real-world applications customers use.

“The key,” Boateng added, “is to not be scared to embrace big, ambiguous challenges.”

In addition to his PhD program at ETH Zurich, where he’s working on multi-modal emotion detection using sensor data from smartphones and smartwatches, Boateng is currently a visiting researcher at the University of Cambridge, where he’s exploring collaborations on AI-powered mobile health research. He remains focused on building SuaCode.ai while exploring mobile and wearable technologies in pervasive health.

“I’m passionate about using technology to help people live healthier lives,” said Boateng, who plans to pursue a postdoctoral research fellowship and hopes to become a professor. “I’m grateful for the opportunity to intern at Amazon. All of the lessons I learned will serve me well in the next chapter of my career and life.”

Amazon is looking for science interns around the world, click the button below to browse and apply for the latest open positions.

Related content

US, NY, New York
We are seeking an Applied Scientist to develop and optimize Visual Inertial Odometry (VIO) and sensor fusion systems for our intelligent robots. In this role, you will design, implement, and deploy state estimation and tracking algorithms that enable robots to understand their position and motion in real time, even in challenging and dynamic environments. You will own the full pipeline from algorithm development through embedded deployment, ensuring that perception systems run efficiently on resource-constrained robotic hardware. You will also leverage modern machine learning approaches to push the boundaries of classical perception methods, combining learned representations with geometric techniques to achieve robust, real-time performance. This is a deeply hands-on role. You will work directly with sensors, hardware, and real-world data, while prototyping, testing, and iterating in physical environments. The ideal candidate has strong foundations in VIO and sensor fusion, practical experience optimizing algorithms for embedded platforms, and familiarity with how modern deep learning is transforming perception. Key job responsibilities - Design and implement Visual Inertial Odometry algorithms for robust real-time state estimation on robotic platforms like Sprout - Develop multi-sensor fusion pipelines integrating cameras, IMUs, and other sensing modalities for accurate pose tracking - Optimize perception and tracking algorithms for deployment on embedded hardware (e.g., ARM, GPU-accelerated edge devices) under strict latency and power constraints - Apply modern ML-based perception techniques (learned features, depth estimation, neural odometry) to complement and improve classical geometric approaches - Build and maintain calibration, evaluation, and benchmarking infrastructure for perception systems - Collaborate with hardware, controls, and navigation teams to integrate perception outputs into the robot’s autonomy stack - Lead technical projects from research prototyping through production deployment
US, WA, Seattle
Amazon's Worldwide Pricing & Promotions organization is seeking a talented, hands-on Research Scientist to join the Pricing and Promotion Optimization Science (P2OS) team — the optimization "application layer" within Amazon's Pricing Sciences organization. Amazon adjusts prices on hundreds of millions of products daily across a global marketplace; P2OS is the team that makes those prices optimal. P2OS is a small, specialized unit with an outsized charter: develop and maintain the models that determine optimal prices and promotions across Amazon's catalog and merchant programs. We own the full optimization stack — from price prediction to promotion targeting to competitiveness guardrails — and we measure success in terms of accretive Gross Contribution and Customer Pricing Perception (GCCP). Our work spans Retail Core, Amazon Business, Fresh, Grocery, and international marketplaces, and we are continually investing in more extensible, generalizable science foundations to keep pace with a growing and evolving business. We are looking for an innovative, organized, and customer-focused scientist with exceptional machine learning and predictive modeling skills, causal and experimental evaluation experience, and the entrepreneurial spirit to apply state-of-the-art methods to some of the most impactful pricing problems in e-commerce. You should be comfortable with ambiguity, motivated by measurable business impact, and excited by the opportunity to work at Amazon-scale. Key job responsibilities * Innovate and build. Design, develop, and deploy machine learning models that set optimal prices and promotions across Amazon's global catalog. Own models end-to-end — from problem formulation and data analysis through offline evaluation, A/B testing, and production launch. * Build a generalizable science foundation. Develop models and evaluation frameworks designed to scale across merchant programs, product categories, and marketplaces — enabling cross-learning and reducing the time and cost of applying science to new business contexts. * Build and evolve optimization systems. Design and improve optimization systems — including reinforcement learning and multi-objective optimization approaches — that automate price and promotion decisions at scale across millions of products. * Apply generative AI and foundation models. Identify and pursue opportunities to leverage large language models, embeddings, and generative AI techniques in pricing science — from enriching product representations and extracting competitive signals from unstructured data, to building more capable and explainable pricing systems. * Experiment rigorously. Design and execute A/B tests and causal inference studies to measure the business and customer impact of pricing model changes. Translate findings into production-ready science improvements. * Stay at the frontier. Establish mechanisms to track the latest advances in reinforcement learning, causal ML, multi-objective optimization, generative AI, and demand modeling — and identify opportunities to apply them to Pricing & Promotions business problems. * See the big picture. Contribute to the long-term scientific vision for how Amazon sets competitive, perception-preserving prices — balancing profitability, customer trust, and marketplace health.
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 biology. 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. Key job responsibilities - Build, adapt and evaluate ML models for life sciences applications - Collaborate with a cross-functional team of ML scientists, biologists, software engineers and product managers
US, WA, Seattle
Applied Scientists in AWS Automated Reasoning are dedicated to making AWS the best computing service in the world for customers who require advanced and rigorous solutions for automated reasoning, privacy, and sovereignty. Key job responsibilities - Solve large or significantly complex problems that require deep knowledge and understanding of your domain and scientific innovation. - Own strategic problem solving, and take the lead on the design, implementation, and delivery for solutions that have a long-term quantifiable impact. - Provide cross-organizational technical influence, increasing productivity and effectiveness by sharing your deep knowledge and experience. - Develop strategic plans to identify fundamentally new solutions for business problems. - Assist in the career development of others, actively mentoring individuals and the community on advanced technical issues.
US, MA, Boston
MULTIPLE POSITIONS AVAILABLE Employer: AMAZON.COM SERVICES LLC Offered Position: Economist III Job Location: Boston, Massachusetts Job Number: AMZ9898444 Position Responsibilities: Mentor and guide the applied scientists and economists in our organization and hold us to a high standard of technical rigor and excellence in science. Design and lead roadmaps for complex science projects to help SP have a delightful selling experience while creating long term value for our shoppers. Work with our engineering partners and draw upon your experience to meet latency and other system constraints. Identify untapped, high-risk technical and scientific directions, and simulate new research directions that you will drive to completion and deliver. Be responsible for communicating our science innovations to the broader internal & external scientific community. Position Requirements: Ph.D. or foreign equivalent degree in Economics or a related field and two years of research or work experience in the job offered or a related occupation. Must have two years of research or work experience in the following skill(s): 1) experience in econometrics including experience with program evaluation, forecasting, time series, panel data, or high dimensional problems; 2) experience with economic theory and quantitative methods; and 3) coding in a scripting language such as R, Python, or similar. Amazon.com is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation. 40 hours / week, 8:00am-5:00pm, Salary Range $159,200/year to $215,300/year. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, visit: https://www.aboutamazon.com/workplace/employee-benefits.#0000
US, CA, San Francisco
Amazon is on a mission to redefine the future of automation — and we're looking for exceptional talent to help lead the way. We are building the next generation of advanced robotic systems that seamlessly blend cutting-edge AI, sophisticated control systems, and novel mechanical design to create adaptable, intelligent automation solutions capable of operating safely alongside humans in dynamic, real-world environments. At Amazon, we leverage the power of machine learning, artificial intelligence, and advanced robotics to solve some of the most complex operational challenges at a scale unlike anywhere else in the world. Our fleet of robots spans hundreds of facilities globally, working in sophisticated coordination to deliver on our promise of customer excellence — and we're just getting started. As a Sr. Scientist in Robot Navigation, you will be at the forefront of this transformation — architecting and delivering navigation systems that are intelligent, safe, and scalable. You will bring deep expertise in learning-based planning and control, a strong understanding of foundation models and their application to embodied agents, and as well as have in-depth understanding of control-theoretic approaches such as model predictive control (MPC)-based trajectory planning. You will develop navigation solutions that seamlessly blend data-driven intelligence with principled control-theoretic guarantees. Our vision is bold: to build navigation systems that allow robots to move fluidly and safely through dynamic environments — understanding context, anticipating change, and adapting in real time. You will lead research that bridges the gap between cutting-edge academic advances and production grade deployment, collaborating with world-class teams pushing the boundaries of robotic autonomy, manipulation, and human-robot interaction. Join us in building the next generation of intelligent navigation systems that will define the future of autonomous robotics at scale. Key job responsibilities - Design, develop, and deploy perception algorithms for robotics systems, including object detection, segmentation, tracking, depth estimation, and scene understanding - Lead research initiatives in computer vision, sensor fusion and 3D perception - Collaborate with cross-functional teams including robotics engineers, software engineers, and product managers to define and deliver perception capabilities - Drive end-to-end ownership of ML models — from data collection and labeling strategy to training, evaluation, and deployment - Mentor junior scientists and engineers; contribute to a culture of technical excellence - Define and track key metrics to measure perception system performance in real-world environments - Publish research findings in top-tier venues (CVPR, ICCV, ECCV, ICRA, NeurIPS, etc.) and contribute to patents A day in the life - Train ML models for deployment in simulation and real-world robots, identify and document their limitations post-deployment - Drive technical discussions within your team and with key stakeholders to develop innovative solutions to address identified limitations - Actively contribute to brainstorming sessions on adjacent topics, bringing fresh perspectives that help peers grow and succeed — and in doing so, build lasting trust across the team - Mentor team members while maintaining significant hands-on contribution to technical solutions About the team Our team is a group is a diverse group of scientists and engineers passionate about building intelligent machines. We value curiosity, rigor, and a bias for action. We believe in learning from failure and iterating quickly toward solutions that matter.
GB, London
Are you excited about using econometrics, experimentation, and machine learning to impact real-world business decisions? We are looking for an Economist II to work on challenging problems at the intersection of causal inference and machine learning for Prime Video Ads. You will design experiments, build econometric and ML models, and translate findings into decisions that shape how millions of customers experience advertising on Prime Video. If you have a deeply quantitative approach to problem-solving, enjoy building and implementing models end-to-end, and want to work on problems where rigorous economics meets production-scale ML, we want to talk to you. Key job responsibilities - Design, execute, and analyze experiments to measure the impact of ad policies on customer behavior and business outcomes - Develop causal inference models (experimental and observational) to estimate short- and long-term effects of strategic initiatives - Collaborate with scientists, engineers, and product teams to deliver measurable business impact - Influence business leaders based on empirical findings
US, MA, Boston
Applied Scientists in AWS Automated Reasoning are dedicated to making AWS the best computing service in the world for customers who require advanced and rigorous solutions for automated reasoning, privacy, and sovereignty. Key job responsibilities The successful candidate will: - Solve large or significantly complex problems that require deep knowledge and understanding of your domain and scientific innovation. - Own strategic problem solving, and take the lead on the design, implementation, and delivery for solutions that have a long-term quantifiable impact. - Provide cross-organizational technical influence, increasing productivity and effectiveness by sharing your deep knowledge and experience. - Develop strategic plans to identify fundamentally new solutions for business problems. - Assist in the career development of others, actively mentoring individuals and the community on advanced technical issues. A day in the life This is a unique and rare opportunity to get in early on a fast-growing segment of AWS and help shape the technology, product and the business. You will have a chance to utilize your deep technical experience within a fast moving, start-up environment and make a large business and customer impact. About the team Diverse Experiences Amazon Automated Reasoning 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 Automated Reasoning? At Amazon, automated reasoning is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for automated reasoning across all of Amazon's products and services. We offer talented automated reasoning 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 Automated Reasoning, 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 automated reasoning 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, MA, Boston
Applied Scientists in AWS Automated Reasoning are dedicated to making AWS the best computing service in the world for customers who require advanced and rigorous solutions for automated reasoning, privacy, and sovereignty. Key job responsibilities The successful candidate will: - Solve large or significantly complex problems that require deep knowledge and understanding of your domain and scientific innovation. - Own strategic problem solving, and take the lead on the design, implementation, and delivery for solutions that have a long-term quantifiable impact. - Provide cross-organizational technical influence, increasing productivity and effectiveness by sharing your deep knowledge and experience. - Develop strategic plans to identify fundamentally new solutions for business problems. - Assist in the career development of others, actively mentoring individuals and the community on advanced technical issues. A day in the life This is a unique and rare opportunity to get in early on a fast-growing segment of AWS and help shape the technology, product and the business. You will have a chance to utilize your deep technical experience within a fast moving, start-up environment and make a large business and customer impact. About the team Diverse Experiences Amazon Automated Reasoning 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 Automated Reasoning? At Amazon, automated reasoning is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for automated reasoning across all of Amazon's products and services. We offer talented automated reasoning 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 Automated Reasoning, 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 automated reasoning 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, TX, Austin
Applied Scientists in AWS Automated Reasoning are dedicated to making AWS the best computing service in the world for customers who require advanced and rigorous solutions for automated reasoning, privacy, and sovereignty. Key job responsibilities The successful candidate will: - Solve large or significantly complex problems that require deep knowledge and understanding of your domain and scientific innovation. - Own strategic problem solving, and take the lead on the design, implementation, and delivery for solutions that have a long-term quantifiable impact. - Provide cross-organizational technical influence, increasing productivity and effectiveness by sharing your deep knowledge and experience. - Develop strategic plans to identify fundamentally new solutions for business problems. - Assist in the career development of others, actively mentoring individuals and the community on advanced technical issues. A day in the life This is a unique and rare opportunity to get in early on a fast-growing segment of AWS and help shape the technology, product and the business. You will have a chance to utilize your deep technical experience within a fast moving, start-up environment and make a large business and customer impact. About the team Diverse Experiences Amazon Automated Reasoning 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 Automated Reasoning? At Amazon, automated reasoning is central to maintaining customer trust and delivering delightful customer experiences. Our organization is responsible for creating and maintaining a high bar for automated reasoning across all of Amazon's products and services. We offer talented automated reasoning 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 Automated Reasoning, 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 automated reasoning 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.