Applied Scientist, AWS Generative AI Innovation Center at Amazon
Get hired in a next generation AI company right now.
"Craiglist for jobs in AI" - Tony Rose
As seen in
🖤🤍 If you like MoAIJobs, give us a shoutout on 𝕏
Filter by:
AGI
GIS
RAG
The Generative AI Innovation Center at AWS helps AWS customers accelerate the use of Generative AI and realize transformational business opportunities. This is a cross-functional team of ML scientists, engineers, architects, and strategists working step-by-step with customers to build bespoke solutions that harness the power of Generative AI.
As an Applied Scientist, you are proficient in designing and developing advanced ML models to solve diverse challenges and opportunities. 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.
We’re looking for ML Applied Scientists capable of using GenAI and other ML/DL techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems.
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.
Key job responsibilities
As an ML Applied Scientist, you will:
- Collaborate with ML scientist and architects to research, design, develop, and evaluate cutting-edge generative AI algorithms to address real-world challenges across industries
- Interact with customers directly to understand the business problem, and help them in defining and implementing generative AI solutions and guide customers on adoption patterns and paths to production
- Work closely with account teams, research scientist teams, and product engineering teams to drive model implementations and new solution
- Create and deliver best practice recommendations, scientific artifacts, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholders
A day in the life
About AWS
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, 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 never stopped innovating — that’s 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, it’s 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 We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll 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 flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud
About the team
The team helps customers imagine and scope the use cases that will create the greatest value for their businesses, select and fine-tune the right models, define paths to navigate technical or business challenges, develop proof-of-concepts, 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.
As an Applied Scientist, you are proficient in designing and developing advanced ML models to solve diverse challenges and opportunities. 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.
We’re looking for ML Applied Scientists capable of using GenAI and other ML/DL techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems.
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.
Key job responsibilities
As an ML Applied Scientist, you will:
- Collaborate with ML scientist and architects to research, design, develop, and evaluate cutting-edge generative AI algorithms to address real-world challenges across industries
- Interact with customers directly to understand the business problem, and help them in defining and implementing generative AI solutions and guide customers on adoption patterns and paths to production
- Work closely with account teams, research scientist teams, and product engineering teams to drive model implementations and new solution
- Create and deliver best practice recommendations, scientific artifacts, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholders
A day in the life
About AWS
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, 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 never stopped innovating — that’s 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, it’s 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 We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll 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 flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud
About the team
The team helps customers imagine and scope the use cases that will create the greatest value for their businesses, select and fine-tune the right models, define paths to navigate technical or business challenges, develop proof-of-concepts, 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.