Machine Learning Engineer, Model Customization, Generative AI Innovation Center
Job Description
The Generative AI Innovation Center at AWS empowers customers to harness state of the art AI technologies for transformative business opportunities. Our multidisciplinary team of strategists, scientists, engineers, and architects collaborates with customers across industries to fine-tune and deploy customized generative AI applications at scale. Additionally, we work closely with foundational model providers to optimize AI models for Amazon Silicon, enhancing performance and efficiency. As an SDE on our team, you will drive the development of custom Large Language Models (LLMs) across languages, domains, and modalities. You will be responsible for fine-tuning state-of-the-art LLMs for diverse use cases while optimizing models for high-performance deployment on AWS’s custom AI accelerators. This role offers an opportunity to innovate at the forefront of AI, tackling end-to-end LLM training pipelines at massive scale and delivering next-generation AI solutions for top AWS clients. Key job responsibilities• Large-Scale Training Pipelines: Design and implement distributed training pipelines for LLMs using tools such as Fully Sharded Data Parallel (FSDP) and DeepSpeed, ensuring scalability and efficiency • LLM Customization & Fine-Tuning: Adapt LLMs for new languages, domains, and vision applications through continued pre-training, fine-tuning, and Reinforcement Learning with Human Feedback (RLHF) • Model Optimization on AWS Silicon: Optimize AI models for deployment on AWS Inferentia and Trainium, leveraging the AWS Neuron SDK and developing custom kernels for enhanced performance • Customer Collaboration: Interact with enterprise customers and foundational model providers to understand their business and technical challenges, co-developing tailored generative AI solutions About the teamABOUT AWS: Diverse Experiences Amazon 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, 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.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. 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.Mentorship and Career GrowthWe’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. AWS Global ServicesAWS Global Services includes experts from across AWS who help our customers design, build, operate, and secure their cloud environments. Customers innovate with AWS Professional Services, upskill with AWS Training and Certification, optimize with AWS Support and Managed Services, and meet objectives with 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’ll join a diverse team of technical experts in dozens of countries who help customers achieve more with the AWS cloud.
Locations
- United States, WA, Seattle, Seattle, WA, United States
- United States, VA, Arlington, Arlington, VA, United States
- United States, WA, Bellevue, Bellevue, WA, United States
- United States, NY, New York, New York, NY, United States
Salary
Salary not disclosed
Estimated Salary Rangehigh confidence
180,000 - 280,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- - 3+ years of non-internship professional software development experienceintermediate
- - 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experienceintermediate
- - Hands-on experience with deep learning and/or machine learning methods (e.g. for training, fine tuning, and inference)intermediate
- - Hands-on experience with generative AI technologyintermediate
Required Qualifications
- - 3+ years of non-internship professional software development experience (experience, 3 years)
- - 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience (experience, 2 years)
- - Bachelor's degree in computer science or equivalent (degree in computer science or equivalent)
- - Hands-on experience with deep learning and/or machine learning methods (e.g. for training, fine tuning, and inference) (experience)
- - Hands-on experience with generative AI technology (experience)
Preferred Qualifications
- - 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience (experience, 3 years)
- - 1+ years of programming with at least one software programming language experience (experience, 1 years)
- - • 1+ years of experience hands-on experience with developing, deploying, or optimizing machine learning models using a recognized ML library or framework (experience, 1 years)
- Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $129,300/year in our lowest geographic market up to $223,600/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. This position will remain posted until filled. Applicants should apply via our internal or external career site. (experience)
Responsibilities
- • Large-Scale Training Pipelines: Design and implement distributed training pipelines for LLMs using tools such as Fully Sharded Data Parallel (FSDP) and DeepSpeed, ensuring scalability and efficiency
- • LLM Customization & Fine-Tuning: Adapt LLMs for new languages, domains, and vision applications through continued pre-training, fine-tuning, and Reinforcement Learning with Human Feedback (RLHF)
- • Model Optimization on AWS Silicon: Optimize AI models for deployment on AWS Inferentia and Trainium, leveraging the AWS Neuron SDK and developing custom kernels for enhanced performance
- • Customer Collaboration: Interact with enterprise customers and foundational model providers to understand their business and technical challenges, co-developing tailored generative AI solutions
- About the team
- ABOUT AWS:
- Diverse Experiences
- Amazon 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, 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.
- 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.
- 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.
- Mentorship and 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.
- AWS Global Services
- AWS Global Services includes experts from across AWS who help our customers design, build, operate, and secure their cloud environments. Customers innovate with AWS Professional Services, upskill with AWS Training and Certification, optimize with AWS Support and Managed Services, and meet objectives with 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’ll join a diverse team of technical experts in dozens of countries who help customers achieve more with the AWS cloud.
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Tags & Categories
Machine Learning Engineer, Model Customization, Generative AI Innovation Center
Job Description
The Generative AI Innovation Center at AWS empowers customers to harness state of the art AI technologies for transformative business opportunities. Our multidisciplinary team of strategists, scientists, engineers, and architects collaborates with customers across industries to fine-tune and deploy customized generative AI applications at scale. Additionally, we work closely with foundational model providers to optimize AI models for Amazon Silicon, enhancing performance and efficiency. As an SDE on our team, you will drive the development of custom Large Language Models (LLMs) across languages, domains, and modalities. You will be responsible for fine-tuning state-of-the-art LLMs for diverse use cases while optimizing models for high-performance deployment on AWS’s custom AI accelerators. This role offers an opportunity to innovate at the forefront of AI, tackling end-to-end LLM training pipelines at massive scale and delivering next-generation AI solutions for top AWS clients. Key job responsibilities• Large-Scale Training Pipelines: Design and implement distributed training pipelines for LLMs using tools such as Fully Sharded Data Parallel (FSDP) and DeepSpeed, ensuring scalability and efficiency • LLM Customization & Fine-Tuning: Adapt LLMs for new languages, domains, and vision applications through continued pre-training, fine-tuning, and Reinforcement Learning with Human Feedback (RLHF) • Model Optimization on AWS Silicon: Optimize AI models for deployment on AWS Inferentia and Trainium, leveraging the AWS Neuron SDK and developing custom kernels for enhanced performance • Customer Collaboration: Interact with enterprise customers and foundational model providers to understand their business and technical challenges, co-developing tailored generative AI solutions About the teamABOUT AWS: Diverse Experiences Amazon 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, 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.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. 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.Mentorship and Career GrowthWe’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. AWS Global ServicesAWS Global Services includes experts from across AWS who help our customers design, build, operate, and secure their cloud environments. Customers innovate with AWS Professional Services, upskill with AWS Training and Certification, optimize with AWS Support and Managed Services, and meet objectives with 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’ll join a diverse team of technical experts in dozens of countries who help customers achieve more with the AWS cloud.
Locations
- United States, WA, Seattle, Seattle, WA, United States
- United States, VA, Arlington, Arlington, VA, United States
- United States, WA, Bellevue, Bellevue, WA, United States
- United States, NY, New York, New York, NY, United States
Salary
Salary not disclosed
Estimated Salary Rangehigh confidence
180,000 - 280,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- - 3+ years of non-internship professional software development experienceintermediate
- - 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experienceintermediate
- - Hands-on experience with deep learning and/or machine learning methods (e.g. for training, fine tuning, and inference)intermediate
- - Hands-on experience with generative AI technologyintermediate
Required Qualifications
- - 3+ years of non-internship professional software development experience (experience, 3 years)
- - 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience (experience, 2 years)
- - Bachelor's degree in computer science or equivalent (degree in computer science or equivalent)
- - Hands-on experience with deep learning and/or machine learning methods (e.g. for training, fine tuning, and inference) (experience)
- - Hands-on experience with generative AI technology (experience)
Preferred Qualifications
- - 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience (experience, 3 years)
- - 1+ years of programming with at least one software programming language experience (experience, 1 years)
- - • 1+ years of experience hands-on experience with developing, deploying, or optimizing machine learning models using a recognized ML library or framework (experience, 1 years)
- Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $129,300/year in our lowest geographic market up to $223,600/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. This position will remain posted until filled. Applicants should apply via our internal or external career site. (experience)
Responsibilities
- • Large-Scale Training Pipelines: Design and implement distributed training pipelines for LLMs using tools such as Fully Sharded Data Parallel (FSDP) and DeepSpeed, ensuring scalability and efficiency
- • LLM Customization & Fine-Tuning: Adapt LLMs for new languages, domains, and vision applications through continued pre-training, fine-tuning, and Reinforcement Learning with Human Feedback (RLHF)
- • Model Optimization on AWS Silicon: Optimize AI models for deployment on AWS Inferentia and Trainium, leveraging the AWS Neuron SDK and developing custom kernels for enhanced performance
- • Customer Collaboration: Interact with enterprise customers and foundational model providers to understand their business and technical challenges, co-developing tailored generative AI solutions
- About the team
- ABOUT AWS:
- Diverse Experiences
- Amazon 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, 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.
- 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.
- 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.
- Mentorship and 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.
- AWS Global Services
- AWS Global Services includes experts from across AWS who help our customers design, build, operate, and secure their cloud environments. Customers innovate with AWS Professional Services, upskill with AWS Training and Certification, optimize with AWS Support and Managed Services, and meet objectives with 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’ll join a diverse team of technical experts in dozens of countries who help customers achieve more with the AWS cloud.