Vaga de Data Science Manager, Generative AI Innovation Center
1 vaga: | Publicada em 01/05
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Amazon launched the Generative AI Innovation Center (GAIIC) in Jun 2023 to help
AWS customers accelerate the use of Generative AI to solve business and
operational problems and promote innovation in their organization
tps://press.aboutamazon.com/2023/6/aws-announces-generative-ai-innovation-center).
GAIIC provides opportunities to innovate in a fast-paced organization that
contributes to game-changing projects and technologies that get deployed on
devices and in the cloud. As a Data Science Manager in GAIIC, you'll partner with
technology and business teams to build new GenAI solutions that delight our
customers. You will be responsible for directing a team of data 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
types of data to address real-world problems.
The successful candidate will possess both technical and customer-facing skills
that will allow them to be the technical face of AWS within our solution
providers ecosystem/environment as well as directly to end customers. You will be
able to drive discussions with senior technical and management personnel within
customers and partners, as well as the technical background that enables them to
interact with and give guidance to data/research/applied scientists and software
developers.
The ideal candidate will also have a demonstrated ability to think strategically
about business, product, and technical issues. Finally, and of critical
importance, the candidate will be an excellent technical team manager, someone who
knows how to hire, develop, and retain high quality technical talent.
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.
A day in the life
A day in the life
Here at AWS, we embrace our differences. We are committed to furthering our
culture of inclusion. We have ten employee-led affinity groups, reaching 40,000
employees in over 190 chapters globally. We have innovative benefit offerings, and
host annual and ongoing learning experiences, including our Conversations on Race
and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazons culture
of inclusion is reinforced within our 16 Leadership Principles, which remind team
members to seek diverse perspectives, learn and be curious, and earn trust.
About the team
Work/Life Balance
Our team puts a high value on work-life balance. It isnt about how many hours you
spend at home or at work; its about the flow you establish that brings energy to
both parts of your life. We believe striking the right balance between your
personal and professional life is critical to life-long happiness and fulfillment.
We offer flexibility in working hours and encourage you to find your own balance
between your work and personal lives.
Mentorship & Career Growth
Our team is dedicated to supporting new members. We have a broad mix of experience
levels and tenures, and were building an environment that celebrates knowledge
sharing and mentorship. Our senior members enjoy one-on-one mentoring and
thorough, but kind, code reviews. We care about your career growth and strive to
assign projects based on what will help each team member develop into a
better-rounded engineer and enable them to take on more complex tasks in the
future.
We are open to hiring candidates to work out of one of the following locations:
Sao Paulo, SP, BRA
- 5+ years of data science or data science management experience
- 3+ years of experience managing data scientists or machine learning engineers
- Knowledge of ML, NLP, Information Retrieval and Analytics
- Experience directly managing scientists or machine learning engineers