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Machine Learning University Applied Scientist

Job ID: 1776083 | Amazon Development Center DEU


Machine Learning (ML) has been strategic to Amazon from the early years. We are pioneers in areas such as recommendation engines, product search, eCommerce fraud detection, and large-scale optimization of fulfillment center operations.

Machine Learning University’s (MLU) mission is to teach people to apply ML to business and operational challenges. In service of this goal, we are growing our presence outside the US, and are looking to hire in EMEA region. We believe strongly that a practical knowledge of ML can be taught broadly, and is a key skill for many builders to learn. Come join Amazon’s MLU and help spread knowledge of ML!

We have built a team of passionate science educators with the demonstrated ability to explain ML to an audience of technical professionals, enhance curriculum, and collaborate with scientists across the company. You will teach practitioners how to train, tune, and deploy ML models to solve challenges in customer segmentation, fraud prevention, capacity planning, predictive maintenance, pricing optimization, call center analtyics, and event detection among others. Practical experience with machine learning is key to ensure content is up-to-date, practical and engaging. This is a full-time role where you will constantly be challenged to learn and be curious about ML.

As a MLU Applied Scientist on our team, you would have the following responsibilities:
· Teach customers directly to understand their business problems, and help them with defining and implementing scalable ML/DL solutions to solve them
· Develop open-source curriculum designed to provide a practical knowledge of ML. This includes lectures, videos, demos, and coding notebook assignments (find an article about our largest release here:
· Collaborate with scientists across Amazon to continuously understand and integrate advances in ML into the curriculum
· Help drive high-level curriculum decisions to ensure alignment with students’ needs and the state-of-the-art domains of advancement in ML
· Consult with customers on model development and deployment best practices by using computer science fundamentals

This team is comprised of Data Scientists, Applied Scientists and Instructional Designers to create first-in-class courses and learning assets in practical ML. The role may require travel up to 40% of the time (pending safety protocols and travel restrictions). We are currently recruiting for talented individuals for this role in the following cities: London, Cambridge, Tuebingen, Dublin, Amsterdam, Berlin, Paris, or Gdansk. Let’s bring ML to everyone and demystify and democratize technology together!

Inclusive Team Culture
Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences.

Work/Life Balance
Our team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfilment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.

Mentorship & Career Growth
Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. We Hire and Develop the best so you can expect support in advancing your career ambitions and projects which will help you grow and develop your skills.


· Master's degree (or equivalent) or PhD degree in Data Science, Computer Science, Machine Learning, Mathematics, Engineering or related technical/scientific field
· Relevant experience in building machine learning or deep learning models and/or systems in a production environment
· Working knowledge of at least one programming language, such as Python, Java, C++, etc., and with demonstrable experience developing machine learning solutions in that language
· Experience teaching a technical topic in either an academic of business setting
· Experience in customer-facing or consultative roles
· Experience hiring or mentoring junior colleagues
· Ability to travel up to 40%


· PhD degree in Data Science, Computer Science, Machine Learning, Mathematics, Engineering or related technical/scientific field
· Experience teaching Machine Learning skills to academic or corporate learners
· Experience with application of methods of Machine Learning
· Proven communication skills, presentation skills, and attention to detail
· Knowledge of Python and associated ML libraries, particularly NumPy, Pandas, Matplotlib, Scikit Learn, and a deep learning framework (MXNet, PyTorch, Tensorflow, etc.)