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Senior Applied Science Manager, AWS Generative AI Innovation Center

2 mesi fa


Milano, Lombardia, Italia Amazon A tempo pieno
About the Role

We are seeking a highly skilled and experienced Senior Applied Science Manager to join our AWS Generative AI Innovation Center team. As a key member of our team, you will be responsible for driving the adoption of generative AI solutions across our customer base.

Key Responsibilities
  1. Customer Engagement: Work directly with customers to understand their business needs and guide them in implementing generative AI solutions.
  2. Team Leadership: Develop and lead a team of data scientists, deep learning architects, and ML engineers to build and deploy generative AI models and pipelines.
  3. Strategic Partnerships: Collaborate with cross-functional teams to identify opportunities for building reusable technical assets and provide customer and market feedback to inform product direction.
  4. Revenue Growth: Drive revenue growth across a broad set of customers by developing and executing strategic plans to increase adoption of generative AI solutions.
  5. Thought Leadership: Establish yourself as a thought leader in the field of generative AI and drive value creation for our customers through the development of technical solutions and strategic partnerships.
About the Team

Our team is responsible for building and deploying generative AI solutions that delight our customers. As a Senior Applied Science Manager, you will be part of a fast-paced organization that contributes to game-changing projects and technologies. You will have the opportunity to work with a diverse range of customers and partners to develop and deploy innovative solutions.

Requirements
  1. PhD or MSc in Computer Science or related technical field
  2. Several years of experience in managing scientists or machine learning engineers
  3. Knowledge of ML, NLP, Information Retrieval, and Analytics
  4. Ability to demonstrate senior stakeholder management skills and collaborate effectively with multidisciplinary teams
  5. Experience directly managing scientists or machine learning engineers
  6. Ability to translate informal customer requirements into problem definitions, dealing with ambiguity and competing objectives
Preferred Qualifications
  1. Experience building machine learning models or developing algorithms for business applications
  2. Experience building complex software systems, especially involving deep learning, machine learning, and computer vision
  3. Deep expertise in generative AI and hands-on experience of deploying and hosting Large Foundational Models
  4. Experience and deep knowledge of AWS and AWS AI/ML services
  5. Excellent written and verbal communication skills with the ability to present complex technical information in a clear and concise manner
  6. Project management experience working on cross-functional projects