Amazon launched the Generative AI Innovation Center (GenAIIC) in June 2023 to help AWS customers accelerate the use of generative AI to solve business and operational problems and promote innovation in their organization. This is a team of strategists data scientists engineers and solution architects working stepbystep with customers to build bespoke solutions that harness the power of generative AI. generativeaiinnovationcenter).
Were looking for Data Scientists to use generative AI and other techniques to design evangelize and implement stateoftheart solutions for neverbeforesolved problems.
You will work directly with customers and innovate in a fastpaced organization that contributes to gamechanging projects and technologies. You will design and run experiments research new algorithms and find new ways of optimizing risk profitability and customer experience.
As an earlyincareer joiner you will initially join our A2C (Associate to Consultant) program for intensive training on AWS technology and delivery approach.
Emirati nationality is required.
Key job responsibilities
As a Data Scientist you will
Collaborate with AI/ML scientists engineers and architects to Research design develop and evaluate cuttingedge generative AI algorithms to address realworld challenges
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 to production
Create and deliver best practice recommendations tutorials blog posts sample code and presentations adapted to technical business and executive stakeholder
Provide customer and market feedback to Product and Engineering teams to help define product direction
About the team
The team helps customers imagine and scope the use cases that will create the greatest value for their businesses select and train or fine tune the right models define paths to navigate technical or business challenges develop proofofconcepts and make plans for launching solutions at scale. The Generative AI Innovation Center team provides guidance on best practices for applying generative AI responsibly and cost efficiently.
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description we encourage candidates to apply. If your career is just starting hasnt followed a traditional path or includes alternative experiences dont let it stop you from applying.
Why AWS
Amazon Web Services (AWS) is the worlds most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating thats why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Inclusive Team Culture
Here at AWS its in our nature to learn and be curious. Our employeeled affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences inspire us to never stop embracing our uniqueness.
Mentorship & Career Growth
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Work/Life Balance
We value worklife harmony. Achieving success at work should never come at the expense of sacrifices at home which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home theres nothing we cant achieve in the cloud.
Bachelors degree or Masters degree or equivalent experience
Experience building a range of AI/ML models
Experience in any of the following areas: algorithms and data structures parsing numerical optimization data mining parallel and distributed computing highperformance computing neural deep learning methods and/or machine learning
Experience in using Python and hands on experience building models with deep learning frameworks like Tensorflow Keras PyTorch MXNet
Prior experience in training and finetuning of Large Language Models (LLMs)
Knowledge of AWS platform and tools
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