Applied Scientist III, 5365 - CMT Systems
DESCRIPTION
Applied Scientist, CMT, Amazon Bangalore
Impact
As a member of the CMT team, you'll play a key role in the evolution of our Competitive Monitoring systems to solve significantly complex and interesting technical challenges in Large-scale computing, Distributed systems, Web applications, Data mining, Scalability, Security, and Algorithms to name a few. The team's work directly impacts customer experience at a worldwide scale.
Innovation
Are you seeking an environment where you can drive innovation? Do you want to apply state-of-the-art computer science and advance information retrieval techniques to solve real world problems of competitive data analysis? Does the challenge of building real time, highly scalable solutions for the most complex online business using innovative technology excite you?
Opportunity
To meet these challenges, the CMT team is looking for passionate, talented and innovative scientists looking to work on cutting edge technology, from Natural Language processing to optimization to image processing and LLMs.
In addition to getting the opportunity to participate in research in several domains, you will lead the solution to complex pricing problems in an extremely agile environment. This role will have the opportunity to learn and work on the most cutting edge generative AI solutions.
Come be part of this growing, dynamic and challenging space!
Key job responsibilities
1. Research the problem domain and come up with various approaches to solve the problem.
2. Be willing to experiment quickly and fail fast.
3. Collaborate with engineers to come up with the right end to end solution to the business problems.
4. Ideate on future roadmap for science in CMT, and CMT in general.
BASIC QUALIFICATIONS
- 8+ years of building machine learning models for business application experience
- PhD, or Master's degree and 8+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning
PREFERRED QUALIFICATIONS
- 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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