Amazon Web Services (AWS)
Machine Learning Engineer – Generative AI Innovation Center
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Machine Learning Engineer
role at
Amazon Web Services (AWS) .
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.
Key Responsibilities
Design and implement distributed training pipelines for LLMs using tools such as Fully Sharded Data Parallel (FSDP) and DeepSpeed, ensuring scalability and efficiency.
Adapt LLMs for new languages, domains, and vision applications through continued pre‑training, fine‑tuning, and Reinforcement Learning with Human Feedback (RLHF).
Optimize AI models for deployment on AWS Inferentia and Trainium, leveraging the AWS Neuron SDK and developing custom kernels for enhanced performance.
Interact with enterprise customers and foundational model providers to understand their business and technical challenges, co‑developing tailored generative AI solutions.
About the Team 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.
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.
We value work‑life harmony and 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.
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.
Basic Qualifications
Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field.
2+ years of professional software development experience.
2+ years of non‑internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience.
Hands‑on experience with deep learning and machine learning methods (e.g., for training, fine‑tuning, and inference).
Hands‑on experience with generative AI technology.
Preferred Qualifications
Experience with training and deploying machine learning systems to solve large‑scale optimizations, or experience in software development.
2+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience.
Hands‑on experience with at least one ML library or framework.
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
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Machine Learning Engineer
role at
Amazon Web Services (AWS) .
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.
Key Responsibilities
Design and implement distributed training pipelines for LLMs using tools such as Fully Sharded Data Parallel (FSDP) and DeepSpeed, ensuring scalability and efficiency.
Adapt LLMs for new languages, domains, and vision applications through continued pre‑training, fine‑tuning, and Reinforcement Learning with Human Feedback (RLHF).
Optimize AI models for deployment on AWS Inferentia and Trainium, leveraging the AWS Neuron SDK and developing custom kernels for enhanced performance.
Interact with enterprise customers and foundational model providers to understand their business and technical challenges, co‑developing tailored generative AI solutions.
About the Team 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.
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.
We value work‑life harmony and 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.
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.
Basic Qualifications
Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field.
2+ years of professional software development experience.
2+ years of non‑internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience.
Hands‑on experience with deep learning and machine learning methods (e.g., for training, fine‑tuning, and inference).
Hands‑on experience with generative AI technology.
Preferred Qualifications
Experience with training and deploying machine learning systems to solve large‑scale optimizations, or experience in software development.
2+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience.
Hands‑on experience with at least one ML library or framework.
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
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