Senior Machine Learning Engineer, Model Customization, Generative AI Innovation
Amazon, Los Angeles, CA, United States
Job ID: 3141363 | Amazon Web Services, Inc.
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. We also 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 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 5+ years of non‑internship professional software development experience.
5+ years of programming with at least one software programming language experience.
5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience.
Experience as a mentor, tech lead or leading an engineering team.
Hands‑on experience with deep learning and machine learning methods (e.g., for training, fine tuning, and inference).
Experience with design, development, and optimization of generative AI solutions, algorithms, or technologies.
Preferred Qualifications 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience.
Bachelor's degree in computer science or equivalent.
2+ years of building machine learning models or developing algorithms for business application 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.
Compensation: The base pay for this position ranges from $151,300/year in our lowest geographic market up to $261,500/year in our highest geographic market. Equity, sign‑on payments, and other compensation may be provided as part of a total compensation package.
Location: US, Massachusetts, North Reading
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In Summary: The Generative AI Innovation Center at AWS empowers customers to harness state‑of‑the‑art AI technologies for transformative business opportunities . The 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 .
En Español: ID de trabajo: 3141363 Amazon Web Services, Inc. El Centro de Innovación en IA Generativa de AWS permite a los clientes aprovechar las tecnologías AI más avanzadas para oportunidades empresariales transformadoras. Nuestro equipo multidisciplinario de estrategas, científicos, ingenieros y arquitectos colabora con clientes en todas las industrias para ajustar y implementar aplicaciones generativas de IA personalizadas a escala. También trabajamos estrechamente con proveedores de modelos fundamentales para optimizar modelos de IA para Amazon Silicon, mejorando el rendimiento y la eficiencia. Como SDE en nuestro equipo, impulsará el desarrollo de Modelos Large Language (LLM) personalizados en diferentes idiomas, dominios y modalidades. Usted será responsable del ajuste fino del estado de los LL-artMs para casos de uso al tiempo que optimiza diversos modelos de implementación de alto rendimiento en aceleradores de IA de AWS personalizados. Esta función ofrece una oportunidad para innovar a la vanguardia de la IA, abordando pipelines de capacitación LLM de extremo a extremo en escala masiva y ofreciendo soluciones AI de próxima generación para los principales clientes de AWS. Principales Responsabilidades Pipelines: Diseño e implementación de tuberías de formación distribuidas para LLMs utilizando herramientas como Full Sharded Data Parallel (FSDP) y DeepSpeed, garantizando escalabilidad y eficiencia. Se pueden proporcionar fondos propios, pagos de suscripción y otras compensaciones como parte del paquete total de indemnización.
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. We also 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 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 5+ years of non‑internship professional software development experience.
5+ years of programming with at least one software programming language experience.
5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience.
Experience as a mentor, tech lead or leading an engineering team.
Hands‑on experience with deep learning and machine learning methods (e.g., for training, fine tuning, and inference).
Experience with design, development, and optimization of generative AI solutions, algorithms, or technologies.
Preferred Qualifications 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience.
Bachelor's degree in computer science or equivalent.
2+ years of building machine learning models or developing algorithms for business application 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.
Compensation: The base pay for this position ranges from $151,300/year in our lowest geographic market up to $261,500/year in our highest geographic market. Equity, sign‑on payments, and other compensation may be provided as part of a total compensation package.
Location: US, Massachusetts, North Reading
#J-18808-Ljbffr
In Summary: The Generative AI Innovation Center at AWS empowers customers to harness state‑of‑the‑art AI technologies for transformative business opportunities . The 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 .
En Español: ID de trabajo: 3141363 Amazon Web Services, Inc. El Centro de Innovación en IA Generativa de AWS permite a los clientes aprovechar las tecnologías AI más avanzadas para oportunidades empresariales transformadoras. Nuestro equipo multidisciplinario de estrategas, científicos, ingenieros y arquitectos colabora con clientes en todas las industrias para ajustar y implementar aplicaciones generativas de IA personalizadas a escala. También trabajamos estrechamente con proveedores de modelos fundamentales para optimizar modelos de IA para Amazon Silicon, mejorando el rendimiento y la eficiencia. Como SDE en nuestro equipo, impulsará el desarrollo de Modelos Large Language (LLM) personalizados en diferentes idiomas, dominios y modalidades. Usted será responsable del ajuste fino del estado de los LL-artMs para casos de uso al tiempo que optimiza diversos modelos de implementación de alto rendimiento en aceleradores de IA de AWS personalizados. Esta función ofrece una oportunidad para innovar a la vanguardia de la IA, abordando pipelines de capacitación LLM de extremo a extremo en escala masiva y ofreciendo soluciones AI de próxima generación para los principales clientes de AWS. Principales Responsabilidades Pipelines: Diseño e implementación de tuberías de formación distribuidas para LLMs utilizando herramientas como Full Sharded Data Parallel (FSDP) y DeepSpeed, garantizando escalabilidad y eficiencia. Se pueden proporcionar fondos propios, pagos de suscripción y otras compensaciones como parte del paquete total de indemnización.