Sr. Applied Scientist, Amazon Devices, Device
hace 1 mes
PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning
The Amazon Devices team designs and engineers high-profile consumer electronics, including the best-selling Kindle family of products. We have also produced groundbreaking devices like Fire tablets, Fire TV, Amazon Dash, and Amazon Echo.
What will you help us create?
**The Team**: How often have you had an opportunity to be a founding member of a team that is solving a significant problem through innovative technology? Would you like to know more about how we are envisioning the use of machine learning and GenAI to solve these problems? If this sounds intriguing, then we’d like to talk to you about a role on our team that's tackling a set of problems requiring significant innovation and scaling.
As a Sr. Applied Scientist, you will design, evangelize, and implement state-of-the-art solutions for never-before-solved problems, helping Amazon Device to provide customer great products. This role will be a key member of a Science and Data technology team based in Guadalajara, Mexico. You will work closely with other scientists, machine learning experts, engineers to design and run experiments, research new algorithms, and find new ways to improve Amazon Device Services & Software products. You will partner with technology and product leaders to solve business and technology problems using scientific approaches to build new services that surprise and delight our customers. Our scientists work closely with software engineers to put algorithms into practice. They also work on cross-disciplinary efforts with other scientists within Amazon.
**The key responsibility for this role include**:
- Define proper output business Metrics, and build input models to identify patterns and drivers of the output. Drive actions at scale using scientifically-based methods and decision making.
- Design experiments, test hypotheses, and build actionable models
- Prototype these models by using modeling languages such as R or in software languages such as Python.
- Work with software engineering teams to drive scalable, real-time implementations
- Utilizing Amazon systems and tools to effectively work with terabytes of data
Zapopan, MEX
- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale distributed systems such as Hadoop, Spark etc.
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