Amazon Web Services (AWS)
Startups Sr. Applied Scientist, Generative AI Innovation & Delivery Team
Amazon Web Services (AWS), Santa Clara, California, us, 95053
Overview
Startups Sr. Applied Scientist, Generative AI Innovation & Delivery Team. Do you have deep technical GenAI background in the Startup space? Are you looking to work with world leading startups at the forefront of Generative AI? Join the Generative AI Innovation and Delivery Team (GenAIID) Startup Organization! The Generative AI Innovation and Delivery mission is to drive startup innovation by making AWS the preferred GenAI platform for startups to experiment, build and scale their products. We are a team of strategists, scientists, engineers, and architects working closely with world's leading startups across GenAI model providers, GenAI tooling and applications. We partner closely with startups to address their GenAI infrastructure needs, evolve their GenAI product and infuse GenAI into their existing SaaS applications. In this process we provide guidance on best practices for applying generative AI responsibly and cost efficiently. You will work directly with startups 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.
Responsibilities
Collaborate with AI/ML scientists and engineers to research, design, develop, and evaluate generative AI solutions to address real-world opportunities
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
Develop a deep understanding of startups GenAI ecosystem and their evolving technical needs to drive improvements to startups program and resulting customer experience
Provide customer and market feedback to product and engineering teams to help define product direction
Unlock scale by identifying patterns and establishing reusable assets to accelerate customer impact of future engagements
About The Team AWS Global Services includes experts from across AWS who help our customers design, build, operate, and secure their cloud environments. Our services include AWS Professional Services, AWS Training and Certification, AWS Support and Managed Services, and AWS Security Assurance Services. Our expertise and emerging technologies include AWS Partners, AWS Sovereign Cloud, AWS International Product, and the Generative AI Innovation Center. You will join a diverse team of technical experts in dozens of countries who help customers achieve more with the AWS cloud.
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.
About 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 AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do.
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, there’s nothing we can’t achieve in the cloud.
Mentorship & Career Growth We are continuously raising our performance bar as we strive to become Earth\'s Best Employer. That is why you will find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
Basic Qualifications
PhD, or Master\'s degree and 6+ years of applied research experience
5+ years of hands on experience with Python to build, train, and evaluate models
5+ years of 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 of experience with design, development, and optimization of generative AI solutions, algorithms, or technologies
Experience in patents or publications at peer-reviewed conferences or journals
Preferred Qualifications
Experience working in a startup or with startup customers
2+ years of experience with design, deployment, and evaluation of Large Language Model (LLM)-powered agents and tools and orchestration approaches
Hands-on experience with model customization techniques such as fine-tuning, continued pre-training, and LLM-as-judge evaluation
Experience with optimization of models on GPUs, Amazon Silicon, or TPUs
2+ years of experience with open source frameworks for building applications powered by LLMs like LangChain, LlamaIndex, and/ or similar tools
Experience building generative AI applications on AWS using services such as Amazon Bedrock and Amazon SageMaker
Strong communication skills, with attention to detail and ability to convey rigorous technical concepts and considerations to non-experts
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
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 https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you\'re applying in isn\'t listed, please contact your Recruiting Partner.
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Responsibilities
Collaborate with AI/ML scientists and engineers to research, design, develop, and evaluate generative AI solutions to address real-world opportunities
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
Develop a deep understanding of startups GenAI ecosystem and their evolving technical needs to drive improvements to startups program and resulting customer experience
Provide customer and market feedback to product and engineering teams to help define product direction
Unlock scale by identifying patterns and establishing reusable assets to accelerate customer impact of future engagements
About The Team AWS Global Services includes experts from across AWS who help our customers design, build, operate, and secure their cloud environments. Our services include AWS Professional Services, AWS Training and Certification, AWS Support and Managed Services, and AWS Security Assurance Services. Our expertise and emerging technologies include AWS Partners, AWS Sovereign Cloud, AWS International Product, and the Generative AI Innovation Center. You will join a diverse team of technical experts in dozens of countries who help customers achieve more with the AWS cloud.
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.
About 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 AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do.
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, there’s nothing we can’t achieve in the cloud.
Mentorship & Career Growth We are continuously raising our performance bar as we strive to become Earth\'s Best Employer. That is why you will find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
Basic Qualifications
PhD, or Master\'s degree and 6+ years of applied research experience
5+ years of hands on experience with Python to build, train, and evaluate models
5+ years of 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 of experience with design, development, and optimization of generative AI solutions, algorithms, or technologies
Experience in patents or publications at peer-reviewed conferences or journals
Preferred Qualifications
Experience working in a startup or with startup customers
2+ years of experience with design, deployment, and evaluation of Large Language Model (LLM)-powered agents and tools and orchestration approaches
Hands-on experience with model customization techniques such as fine-tuning, continued pre-training, and LLM-as-judge evaluation
Experience with optimization of models on GPUs, Amazon Silicon, or TPUs
2+ years of experience with open source frameworks for building applications powered by LLMs like LangChain, LlamaIndex, and/ or similar tools
Experience building generative AI applications on AWS using services such as Amazon Bedrock and Amazon SageMaker
Strong communication skills, with attention to detail and ability to convey rigorous technical concepts and considerations to non-experts
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
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 https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you\'re applying in isn\'t listed, please contact your Recruiting Partner.
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