Senior Applied Scientist, Digital Acceleration
DESCRIPTION
Key Job Responsibilities
- Research, experiment and build Proof Of Concepts advancing the state of the art in AI & ML.
- Collaborate with cross-functional teams to architect and execute technically rigorous AI projects.
- Thrive in dynamic environments, adapting quickly to evolving technical requirements and deadlines.
- Engage in effective technical communication (written & spoken) with coordination across teams.
- Conduct thorough documentation of algorithms, methodologies, and findings for transparency and reproducibility.
- Publish research papers in internal and external venues of repute.
- Support on-call activities for critical issues.
Basic Qualifications
Experience building machine learning models or developing algorithms for business application.PhD, or a Master's degree and experience in CS, CE, ML or related field.Knowledge of programming languages such as C / C++, Python, Java or Perl.Experience in any of the following areas : algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing.Proficiency in coding and software development, with a strong focus on machine learning frameworks.Understanding of relevant statistical measures such as confidence intervals, significance of error measurements, development and evaluation data sets, etc.Excellent communication skills (written & spoken) and ability to collaborate effectively in a distributed, cross-functional team setting.5+ years of building machine learning models or developing algorithms for business application experience.Experience programming in Java, C++, Python or related language.Experience with neural deep learning methods and machine learning.Preferred Qualifications
5+ years of building machine learning models or developing algorithms for business application experience.Have publications at top-tier peer-reviewed conferences or journals.Track record of diving into data to discover hidden patterns and conducting error / deviation analysis.Ability to develop experimental and analytic plans for data modeling processes, use of strong baselines, ability to accurately determine cause and effect relations.Exceptional level of organization and strong attention to detail.Comfortable working in a fast paced, highly collaborative, dynamic work environment.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.Our inclusive culture empowers Amazonians to deliver the best results for our customers.
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
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