Senior Applied Scientist, Alexa AI
3 weeks ago
Key responsibilities include:
- 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
Basic Qualifications:
- Master's or PhD in computer science, statistics or a related field
- 5+ years experience in deep learning, machine learning, and data science.
- Proficiency in coding and software development, with a strong focus on machine learning frameworks.
- Experience in Python, or another language; command line usage; familiarity with Linux and AWS ecosystems.
- 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.
- Papers published in AI/ML venues of repute
Preferred Qualifications:
- 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
- The motivation to achieve results in a fast-paced environment.
- Exceptional level of organization and strong attention to detail
- Comfortable working in a fast paced, highly collaborative, dynamic work environment
About the team
The team works on building Responsible AI alignment techniques for the Large Language Model (LLM) that drives Alexa+. We work on recent advances in LLM science including automated prompt optimisation, supervised fine tuning, Re-inforcement learning, model distillation, retrieval augmented generation, model & prompt interpretability and LLM driven data generation. The techniques are used to tune a foundational model to align with Alexa's policies on Responsible AI across dimensions of Appropriateness, Safety, Security, Privacy and Fairness. We focus on building cross-lingual methods to support 100s of millions of Alexa customers across the world speaking 15+ languages. A scientist on the team works on the following - a) running experiments to evaluate promising ideas to achieve a customer experience goal; b) Identify a research theme and follow recent advances in the space (papers/articles); c) collaborate with other scientists (within and outside team) to identify a science direction to solve a problem; d) publish papers in peer-reviewed conferences & journals of repute; e) Collaborate with faculty members in Indian academia (e.g. IIT-B).
The team's work was part of the Alexa+ launch announcement: [...]- 5+ years of building machine learning models for business application experience
- PhD, or Master's degree
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning- 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.
- Do you have publications at top-tier peer-reviewed conferences or journals?
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