Applied Scientist II, Artificial Generative Intelligence (AGI)
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