Job Information
Amazon Applied Scientist II, Artificial Generative Intelligence (AGI) in Bengaluru, India
Description
The Amazon Artificial Generative Intelligence (AGI) team in India is seeking a talented, self-driven Applied Scientist to work on prototyping, optimizing, and deploying ML algorithms within the realm of Generative AI.
Key job responsibilities
Research, experiment and build Proof Of Concepts advancing the state of the art in AI & ML for GenAI.
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
We are open to hiring candidates to work out of one of the following locations:
Bengaluru, KA, IND
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.
Preferred Qualifications
3+ 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