Machine Learning Research Scientist

1 month ago

London, Greater London, United Kingdom Amazon Full time
Unlock the Power of Generative AI

Amazon is seeking a highly skilled Machine Learning Research Scientist to join our Generative Artificial Intelligence (AI) Innovation Center team. As a key member of this team, you will have the opportunity to innovate in a fast-paced organization that contributes to game-changing projects and technologies leveraging cutting-edge generative AI algorithms.

Key Responsibilities
  1. Collaborate with scientists and engineers to research, design, and develop cutting-edge generative AI algorithms to address real-world challenges.
  2. Work across customer engagement to understand what adoption patterns for generative AI are working and rapidly share them across teams and leadership.
  3. Interact with customers directly to understand the business problem, help and aid them in implementation of generative AI solutions, deliver briefing and deep dive sessions to customers, and guide customers on adoption patterns and paths for generative AI.
  4. Provide customer and market feedback to Product and Engineering teams to help define product direction.
Requirements
  1. 2+ years of building machine learning models or developing algorithms for business application experience.
  2. Master's degree in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics, or equivalent quantitative field.
  3. Knowledge of programming languages such as C/C++, Python, Java, or Perl.
  4. Proven knowledge of deep learning and experience hosting and deploying ML solutions (e.g., for training, tuning, and inferences).
Preferred Qualifications
  1. PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics, or equivalent quantitative field.
  2. Working knowledge of generative AI and hands-on experience in prompt engineering, deploying, and hosting Large Foundational Models.
  3. Hands-on experience building models with deep learning frameworks like TensorFlow, PyTorch, or MXNet.

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