Amazon Web Services (AWS)
Machine Learning Engineer
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Machine Learning Engineer
role at
Amazon Web Services (AWS)
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
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)
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
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.
#J-18808-Ljbffr