Senior Applied Scientist, Generative AI Innovation Center
Senior Applied Scientist, Generative AI Innovation Center
Posted on :
25-09-2025
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1 Vacancy
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Monthly Salary
Not Disclosed
Salary Not Disclosed
Vacancy
1 Vacancy
Posted on :
25-09-2025
Job Description
Are you looking to work at the forefront of Machine Learning and AI Would you be excited to apply Generative AI algorithms to solve real world problems with significant impact The Generative AI Innovation Center helps AWS customers implement Generative AI solutions and realize transformational business opportunities. This is a team of strategists scientists engineers and architects working step-by-step with customers to build bespoke solutions that harness the power of generative AI.
The team helps customers imagine and scope bespoke use cases that will create the greatest value for their businesses define paths to navigate technical or business challenges develop and optimize models to power their solutions and make plans for launching solutions at scale. The GenAI Innovation Center team provides guidance on best practices for applying generative AI responsibly and cost efficiently.
You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments research new algorithms and find new ways of optimizing risk profitability and customer experience.
Were looking for Applied Scientists capable of using GenAI and other techniques to design evangelize and implement state-of-the-art solutions for never-before-solved problems.
Key job responsibilities
As an Applied Scientist you will
Collaborate with AI/ML scientists and architects to research design develop and evaluate generative AI solutions to address real-world challenges
Interact with customers directly to understand their business problems aid them in implementation of generative AI solutions brief customers and guide them on adoption patterns and paths to production
Help customers optimize their solutions through approaches such as model selection training or tuning right-sizing distillation and hardware optimization
Provide customer and market feedback to product and engineering teams to help define product direction
About the team
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the preferred 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 employee-led 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
Were continuously raising our performance bar as we strive to become Earths Best Employer. Thats why youll find endless knowledge-sharing mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
Work/Life Balance
We value work-life 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.
- PhD degree in computer science engineering mathematics operations research or in a highly quantitative field plus 5 years of relevant experience or Masters degree plus 10 years of relevant work experience
- 5 years of hands on experience with Python to build train and evaluate models
- 5 years of hands on experience in any of the following areas: algorithms and data structures parsing numerical optimization data mining parallel and distributed computing high-performance computing
- 2 years demonstrated experience with Large Language Model (LLM) and Foundational Model post-training continual pre-training fine-tuning or reinforcement learning techniques.
- Scientific publication track record at top-tier AI/ML/NLP conferences or journals
- Demonstrated experience with building LLM-powered agentic workflow orchestration and agent customization
- Experience with model optimization techniques (quantization distillation compression inference optimization etc.)
- Experience with open-source frameworks for model customization like trl verl and for building LLM-powered applications like LangChain LlamaIndex and/ or similar tools
- Track record of leading the design implementation and delivery of scientifically-complex solutions that span multiple teams.
- Experience driving scientific agenda and technical strategy in a team including building consensus on technical approaches and mentoring other scientists to improve their technical capabilities.
Amazon est un employeur engagé pour légalité des chances. Nous sommes convaincus quune main doeuvre diversifée est essentielle à notre réussite. Nous prenons nos décisions de recrutement en fonction de votre expérience et de vos compétences. Nous apprécions votre envie de découvrir dinventer de simplifier et de construire. La protection de votre vie privée et la sécurité de vos données constituent depuis longtemps une priorité absolue pour Amazon. Veuillez consulter notre Politique de Confidentialité pour en savoir plus sur la façon dont nous collectons utilisons et traitons les données personnelles de nos candidats.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process including support for the interview or onboarding process please visit for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.
The team helps customers imagine and scope bespoke use cases that will create the greatest value for their businesses define paths to navigate technical or business challenges develop and optimize models to power their solutions and make plans for launching solutions at scale. The GenAI Innovation Center team provides guidance on best practices for applying generative AI responsibly and cost efficiently.
You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments research new algorithms and find new ways of optimizing risk profitability and customer experience.
Were looking for Applied Scientists capable of using GenAI and other techniques to design evangelize and implement state-of-the-art solutions for never-before-solved problems.
Key job responsibilities
As an Applied Scientist you will
Collaborate with AI/ML scientists and architects to research design develop and evaluate generative AI solutions to address real-world challenges
Interact with customers directly to understand their business problems aid them in implementation of generative AI solutions brief customers and guide them on adoption patterns and paths to production
Help customers optimize their solutions through approaches such as model selection training or tuning right-sizing distillation and hardware optimization
Provide customer and market feedback to product and engineering teams to help define product direction
About the team
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the preferred 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 employee-led 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
Were continuously raising our performance bar as we strive to become Earths Best Employer. Thats why youll find endless knowledge-sharing mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
Work/Life Balance
We value work-life 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.
- PhD degree in computer science engineering mathematics operations research or in a highly quantitative field plus 5 years of relevant experience or Masters degree plus 10 years of relevant work experience
- 5 years of hands on experience with Python to build train and evaluate models
- 5 years of hands on experience in any of the following areas: algorithms and data structures parsing numerical optimization data mining parallel and distributed computing high-performance computing
- 2 years demonstrated experience with Large Language Model (LLM) and Foundational Model post-training continual pre-training fine-tuning or reinforcement learning techniques.
- Scientific publication track record at top-tier AI/ML/NLP conferences or journals
- Demonstrated experience with building LLM-powered agentic workflow orchestration and agent customization
- Experience with model optimization techniques (quantization distillation compression inference optimization etc.)
- Experience with open-source frameworks for model customization like trl verl and for building LLM-powered applications like LangChain LlamaIndex and/ or similar tools
- Track record of leading the design implementation and delivery of scientifically-complex solutions that span multiple teams.
- Experience driving scientific agenda and technical strategy in a team including building consensus on technical approaches and mentoring other scientists to improve their technical capabilities.
Amazon est un employeur engagé pour légalité des chances. Nous sommes convaincus quune main doeuvre diversifée est essentielle à notre réussite. Nous prenons nos décisions de recrutement en fonction de votre expérience et de vos compétences. Nous apprécions votre envie de découvrir dinventer de simplifier et de construire. La protection de votre vie privée et la sécurité de vos données constituent depuis longtemps une priorité absolue pour Amazon. Veuillez consulter notre Politique de Confidentialité pour en savoir plus sur la façon dont nous collectons utilisons et traitons les données personnelles de nos candidats.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process including support for the interview or onboarding process please visit for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.
Required Experience:
Senior IC
Employment Type
Full-Time
Key Skills
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