Aditya Rawal
ML EngineerAI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Principal ML scientist scaling Reinforcement Learning@ Amazon AGI, Previously: Uber AI Labs, PhD@UT Austin
Building scalable RL algorithms for training foundational models, as part of the Artificial General Intelligence team at Amazon. Developed Titan LLMs for AWS Bedrock -- pre-training/fine-tuning/learning-from-human-feedback. Previously worked on Neural Architecture Search, Meta-learning, Network compression, Multi-Agent and Open-ended Reinforcement Learning. I have enjoyed working in diverse teams, building prototype solutions for challenging research problems and publishing in top conferences. Previously, during my PhD thesis, I developed novel meta-learning techniques for training recurrent neural networks.
The University of Texas at Austin
Doctor of Philosophy - PhD, Computer Science
January 1, 2012 – January 1, 2018
The University of Texas at Austin
Masters, Computer Science
January 1, 2009 – January 1, 2012
Netaji Subhas Institute of Technology
Bachelors of Engg., Electronics and Communications
N/A – Present
Amazon AGI Foundations
Principal Machine Learning Scientist
January 1, 2026 – Present
Amazon
Senior ML scientist@ Artificial General Intelligence
January 1, 2024 – December 1, 2025
Amazon Web Services (AWS) AI Labs
Senior Machine Learning Scientist
June 1, 2020 – January 1, 2024
San Francisco Bay Area
Uber AI Labs
Research Scientist
May 1, 2018 – June 1, 2020
San Francisco Bay Area
Sentient Technologies
Research Scientist
July 1, 2016 – May 1, 2018
San Francisco Bay Area
Department of Computer Science, The University of Texas at Austin
Teaching Assistant, Artificial Intelligence
August 1, 2012 – August 1, 2015
Department of Computer Science, The University of Texas at Austin
Graduate Research Assistant
August 1, 2009 – July 1, 2012
Texas instruments
Senior Design Engineer
January 1, 2004 – January 1, 2009
Bengaluru, Karnataka, India
Cultural Fit Analysis
The candidate has worked at several prominent tech companies (Amazon, Uber AI Labs, Sentient Technologies) and has a strong academic background, indicating a drive for innovation and excellence. The diversity of projects, from multimodal foundational models to AI music composers, suggests adaptability and a broad interest in AI applications. This aligns well with a culture that values cutting-edge research and practical implementation.
Soft Skills & Operational Fit
The candidate's resume indicates a strong background in research and development within large organizations, suggesting an ability to work in structured environments and contribute to complex projects. The roles as a Teaching Assistant and Graduate Research Assistant also imply communication and collaboration skills. However, specific soft skill assessments are not available.