Senior Applied Scientist, Generative Artificial Intelligence
1 day ago
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.
As an Applied Scientist, you'll partner with technology and business teams to build solutions that surprise and delight our customers. We’re looking for Applied Scientists capable of using generative AI and other ML techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems.
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. Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholder.
5. Provide customer and market feedback to Product and Engineering teams to help define product direction.
Minimum Requirements
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.
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