Virginia Staffing
Applied Scientist, Model Customization, Generative AI Innovation Center, Model C
Virginia Staffing, Washington, District of Columbia, us, 20022
Generative Ai Innovation Center Applied Scientist
Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to develop 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. Starting in 2024, the Innovation Center launched a new Custom Model and Optimization program to help customers develop and scale highly customized generative AI solutions. 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. We're 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 include: 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 Basic Qualifications: PhD degree in computer science, engineering, mathematics, operations research, or in a highly quantitative field, or Master's degree plus 5 years of relevant work experience 5+ years of hands on experience with Python to build, train, and evaluate models 2+ 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 Experience with design, development, and optimization of generative AI solutions, algorithms, or technologies Scientific publication track record at top-tier AI/ML/NLP conferences or journals Preferred Qualifications: 2+ years demonstrated experience with Large Language Model (LLM) and Foundational Model post-training, continual pre-training, fine-tuning, or reinforcement learning techniques. Demonstrated experience with building LLM-powered agentic workflow, orchestration, and agent customization Track record of building and deploying ML models at scale 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 Hands-on 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, please visit https://amazon.jobs/content/en/how-we-hire/accommodations. If the country/region you're applying in isn't listed, please contact your Recruiting Partner. Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographic market up to $223,400/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits.
Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to develop 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. Starting in 2024, the Innovation Center launched a new Custom Model and Optimization program to help customers develop and scale highly customized generative AI solutions. 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. We're 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 include: 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 Basic Qualifications: PhD degree in computer science, engineering, mathematics, operations research, or in a highly quantitative field, or Master's degree plus 5 years of relevant work experience 5+ years of hands on experience with Python to build, train, and evaluate models 2+ 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 Experience with design, development, and optimization of generative AI solutions, algorithms, or technologies Scientific publication track record at top-tier AI/ML/NLP conferences or journals Preferred Qualifications: 2+ years demonstrated experience with Large Language Model (LLM) and Foundational Model post-training, continual pre-training, fine-tuning, or reinforcement learning techniques. Demonstrated experience with building LLM-powered agentic workflow, orchestration, and agent customization Track record of building and deploying ML models at scale 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 Hands-on 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, please visit https://amazon.jobs/content/en/how-we-hire/accommodations. If the country/region you're applying in isn't listed, please contact your Recruiting Partner. Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographic market up to $223,400/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits.