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Senior Research Scientist

1 month ago

London, Greater London, United Kingdom Amazon Full time
Senior Applied Scientist, Generative Artificial Intelligence (AI) Innovation Center

AWS Sales, Marketing, and Global Services (SMGS) is responsible for driving revenue, adoption, and growth from the largest and fastest growing small- and mid-market accounts to enterprise-level customers including public sector. The AWS Global Support team interacts with leading companies and believes that world-class support is critical to customer success. AWS Support also partners with a global list of customers that are building mission-critical applications on top of AWS services.

The Generative Artificial Intelligence (AI) Innovation Center team at AWS provides opportunities to innovate in a fast-paced organization that contributes to game-changing projects and technologies leveraging cutting-edge generative AI algorithms.

Key Job 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 customer on adoption patterns and paths for generative AI.
  4. Provide customer and market feedback to Product and Engineering teams to help define product direction.
BASIC QUALIFICATIONS
  1. 5+ 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.