Overview
The GenAIIC provides opportunities to innovate in a fast-paced organization that contributes to game-changing projects and technologies deployed on devices and in the cloud. As a Data Science Manager in GenAIIC, you will partner with technology and business teams to build new GenAI solutions that delight our customers.
You will be responsible for directing a team of scientists, deep learning architects, and ML engineers to build generative AI models and pipelines, and deliver state-of-the-art solutions to customers' business and mission problems. Your team will be working with terabytes of text, images, and other data to address real-world problems.
Your role includes being the technical "face" of AWS within our solution providers’ ecosystem/environment as well as directly to end customers. You will drive discussions with senior technical and management personnel within customers and partners, and you will provide the technical background that enables them to interact with and guide data/research/applied scientists and software developers.
The ideal candidate will think strategically about business, product, and technical issues. A critical component of the role is being an excellent technical team manager who can hire, develop, and retain high-quality technical talent.
Responsibilities
* Partner with technology and business teams to build GenAI solutions that deliver value to customers.
* Direct a team of scientists, deep learning architects, and ML engineers to build generative AI models and pipelines and deliver state-of-the-art solutions to customer problems.
* Lead a team working with large-scale data (text, images, and other data) to address real-world use cases.
* Serve as the technical representative of AWS within solution providers’ ecosystems and with end customers.
* Drive discussions with senior technical and management personnel within customers and partners, and guide data/research/applied scientists and software developers.
* Think strategically about business, product, and technical issues; hire, develop, and retain high-quality talent.
Qualifications
* PhD in computer science, mathematics, statistics, machine learning or equivalent quantitative field
* Knowledge of Python or R or other scripting language
* Experience in building quantitative solutions as a scientist or science manager
* Experience directly managing scientists or machine learning engineers
* Experience in applying statistical models for large-scale applications and building automated analytical systems
* Experience in at least one area of Machine Learning (NLP, Regression, Classification, Clustering, or Anomaly Detection)
* Experience with fairness in machine learning and AI to detect and remove bias in ML/AI systems
* Bachelor’s degree in Computer Science or equivalent
About the GenAI Innovation Center
Amazon launched the Generative AI Innovation Center (GenAIIC) in Jun 2023 to help AWS customers accelerate the use of Generative AI to solve business and operational problems and promote innovation. Starting in 2024, the Innovation Center launched a Custom Model and Optimization program to help customers develop and scale highly customized generative AI solutions. The team helps customers imagine and scope bespoke use cases, define paths to navigate challenges, develop and optimize models, and plan for launching solutions at scale. The GenAI Innovation Center team provides guidance on best practices for applying generative AI responsibly and cost efficiently.
Amazon is an equal opportunities employer. We believe that a diverse workforce is central to our success. We make recruiting decisions based on experience and skills. We value passion to discover, invent, simplify and build. We protect privacy and data security as a top priority. Please consult our Privacy Notice to learn how we collect, use and transfer personal data of candidates.
About the team
Diverse Experiences — AWS values diverse experiences. If you do not meet all qualifications, we encourage you to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
Why AWS?
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and continue to innovate, trusted by customers from startups to Global 500 companies.
Inclusive Team Culture
We foster a culture of inclusion with employee-led affinity groups and ongoing events and learning experiences that celebrate diverse perspectives.
Mentorship & Career Growth
We support continuous performance improvement, knowledge sharing, mentorship, and career development resources to help you grow.
Work/Life Balance
We value work-life harmony and strive for flexibility to support your personal and professional success.
#J-18808-Ljbffr