Are you interested in building state-of-the-art machine learning systems for the most complex, and fastest growing, transportation network in the world? If so, Amazon has the most exciting, and never-before-seen, challenges at this scale (including those in sustainability, e.g. how to reach net zero carbon by 2040).
Amazon’s transportation systems get millions of packages to customers worldwide faster and cheaper while providing world class customer experience – from online checkout, to shipment planning, fulfillment, and delivery. Our software systems include services that use tens of thousands of signals every second to make business decisions impacting billions of dollars a year, that integrate with a network of small and large carriers worldwide, that manage business rules for millions of unique products, and that improve experience of over hundreds of millions of online shoppers.
As part of this team you will focus on ML methods and algorithms for core planning systems, as well as for other applications within Amazon Transportation Services. Current research includes machine learning forecast, online reinforcement learning, and anomaly detection models, among others.
We are looking for a Machine Learning Scientist with a strong academic background, and expertise in either of the following:
· Graph Neural Networks (GNNs), Temporal Graph Networks (TGNs), and/or Graph Deep Learning (GDL)
· Probabilistic Machine Learning
At Amazon, we strive to be the most customer-centric company and the best employer on Earth. To continue improving, we need exceptionally talented, bright, and driven people. If you'd like to help us build the place to find and buy anything online, and deliver in the most efficient and greenest way possible, this is your chance to make history.
· PhD in Computer Science, AI, Mathematics, or Statistics with specialization in ML (alternatively, MSc. and 3+ years in a ML scientist role).
· Deep knowledge of fundamentals, and the state-of-the art, in relevant areas of ML.
· 2+ years of hands-on experience in ML research and ML systems.
· Expertise, in any of:
- Graph Neural Networks (GNNs), Temporal Graph Networks (TGNs), and/or Graph Deep Learning (GDL);
- Probabilistic Machine Learning.
· Strong coding skills in Python.
· Experience with cloud computing services such as AWS.
· Experience with programming languages such as Java, Scala, and/or others.
· Experience working effectively with research science, data engineering, and software engineering teams.
· Proven track record of innovation in creating novel algorithms and applying the state-of the-art.
· Strong verbal and written communication skills.
· Strong publication/scientific track record.
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