Applied Scientist: Human and Machine Learning

Amazon’s Global Learning & Development (GLD) Learning Science and Engineering team is growing quickly and is looking for a skilled, driven, applied scientist to develop solutions and innovate at the intersection of human and machine learning.

The Learning Science and Engineering org is reinventing workplace learning by building the programs, products, technologies and mechanisms that make learning effective and scalable for Amazon employees. We use machine learning to augment human decision-making to accelerate and personalize learning and skill development. We have a passion for raising the bar on learning and learning design at Amazon, and simultaneously contributing to the science of human and machine learning. We partner with multiple businesses across Amazon to explore ways to help Amazon employees grow their knowledge and capabilities. We publish research and present our work at internal and external conferences.


We are looking for someone with a passion for learning and experience applying machine learning to augment human decision-making. The role will continuously improve learning programs using an array of creative approaches which drive productivity, innovation, and operational excellence. As an Applied Scientist, you will be working with scientists, engineers, learning designers, product managers, and stakeholders to deliver products or features of products that accelerate learning.

Specific responsibilities include:
· Design, develop, and implement models and solutions to support collaborative learning environments that can help accelerate human learning.
· Deliver Machine Learning solutions to improve learning experiences that can help learners learn more effectively and efficiently.
· Deliver data-driven solutions to assist learning designers to scale up best design practices.
· Deliver innovative and impactful solutions that can solve customer pain points.
· Deliver scientific findings about human learning to the broader science communities.

Basic Qualifications

· Graduate degree in machine learning, computer vision, robotics, or related field.
· 3+ years of industry experience with strong analytic and problem-solving skills.
· Sound theoretical understanding of broad machine learning concepts, with deep and demonstrable expertise in at least one topic or application of machine learning.
· Deep Learning implementation expertise (TensorFlow, PyTorch, MxNet, etc).
· Significant hands-on experience with at least two programming languages (Python, Java, C/C++ or C# or related language).
· Strong verbal and written communication skills.

Preferred Qualifications

· Ph.D. in Computer Science, Machine Learning, Computer Supported Collaborative Learning, Human-Computer Interaction or a highly quantitative field.
· 5+ years of practical experience applying ML to solve complex problems in an applied environment.
· Significant peer-reviewed scientific contributions in premier journals and conferences.
· Strong CS fundamentals in data structures, problem solving, algorithm design and complexity analysis.
· Experience with defining research and development practices in an applied environment.
· Proven track record in technically leading and mentoring scientists.
· Superior verbal and written communication and presentation skills, ability to convey rigorous mathematical concepts and considerations to non-experts.
· Excellent interpersonal communication with strong verbal / written English skills.