Member of Technical Staff - Reinforcement Learning, Agi Autonomy

Amazon Amazon · Big Tech · San Francisco, CA · Applied Science

Research role focused on developing foundational capabilities for AI agents that can act in digital and physical worlds, with a focus on multimodal LLMs, automation agent systems, and applying GenAI to real-world problems. Involves rapid invention, experimentation, and collaboration.

What you'd actually do

  1. Develop multimodal Large Language Models (LLMs) to observe, model and derive insights from manual workflows for automation
  2. Work in a joint scrum with engineers for rapid invention, develop automation agent systems, and take them to launch for millions of customers
  3. Collaborate with cross-functional teams of engineers, product managers, and scientists to identify and solve complex problems in GenAI
  4. Design and execute experiments to evaluate the performance of different algorithms and models, and iterate quickly to improve results
  5. Think big about the arc of development of GenAI over a multi-year horizon, and identify new opportunities to apply these technologies to solve real-world problems

Skills

Required

  • PhD or Master's degree with 5+ years of applied research experience
  • 3+ years of building ML models for business applications
  • Programming in Java, C++, Python or related language
  • Neural deep learning methods and machine learning

Nice to have

  • PhD in Computer Science, Machine Learning, or related field with focus on Gen AI and reinforcement learning
  • Experience developing and implementing algorithms/models for supervised fine-tuning and RLHF
  • Strong Python programming skills
  • Experience with deep learning frameworks (TensorFlow, PyTorch)
  • Excellent problem-solving skills
  • Creative and critical thinking
  • Strong communication and collaboration skills
  • Experience with patents or publications at top-tier conferences/journals

What the JD emphasized

  • PhD
  • Master's degree and 5+ years of applied research experience
  • 3+ years of building machine learning models for business application experience
  • Experience programming in Java, C++, Python or related language
  • Experience with neural deep learning methods and machine learning
  • PhD in Computer Science, Machine Learning, or a related field, with a focus on Gen AI and reinforcement learning
  • Demonstrated experience in developing and implementing algorithms and models for supervised fine-tuning and reinforcement learning through human feedback
  • Strong programming skills in Python and experience with deep learning frameworks such as Tensor Flow or PyTorch
  • Excellent problem-solving skills, with the ability to think creatively and critically about complex problems
  • Strong communication and collaboration skills, with the ability to work effectively with cross-functional teams
  • Experience with patents or publications at top-tier peer-reviewed conferences or journals

Other signals

  • developing new foundational capabilities for AI agents
  • enabling practical AI that can do things
  • high-risk, high-payoff research