DESCRIPTION
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 the development and research of machine learning solutions and algorithms for core planning systems, as well as for other applications within Amazon Transportation Services, and impact the future of the Amazon delivery network. Current research and areas of work within our team include machine learning forecast, anomaly detection models, model interpretability, graph neural nets, among others.
We are looking for a Machine Learning (Applied) Scientist with a strong academic background in the areas of machine learning, time series forecasting, and/or anomaly detection.
At Amazon, we strive to continue being the most customer-centric company on earth. To stay there and 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.
Basic Qualifications
- 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.
- 3+ years of hands-on experience in ML research and ML systems.
- Strong coding skills in Python.
- Strong verbal and written communication skills.
Preferred Qualifications
- 2+ years of experience, and strong expertise, in any of: Probabilistic Machine Learning, time series forecasting, anomaly detection models.
- 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 publication/scientific track record.