Amazon
Overview
AWS Neuron is the complete software stack for the AWS Inferentia and Trainium cloud-scale machine-learning accelerators. This role is for a senior software engineer in the Machine Learning Inference Applications team. This role is responsible for development and performance optimization of core building blocks of LLM Inference - Attention, MLP, Quantization, Speculative Decoding, Mixture of Experts, etc. The team works side by side with chip architects, compiler engineers and runtime engineers to deliver performance and accuracy on Neuron devices across a range of models such as Llama 3.3 70B, 3.1 405B, DBRX, Mixtral, and so on. Responsibilities
Adapt latest research in LLM optimization to Neuron chips to extract best performance from both open source and internally developed models. Collaborate across teams and organizations to deliver optimized solutions for LLM inference on Neuron devices. Develop and optimize core building blocks of LLM inference, including Attention, MLP, Quantization, Speculative Decoding, and Mixture of Experts. About the team
Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge-sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects that help our team members develop your engineering expertise so you feel empowered to take on more complex tasks in the future. Basic Qualifications
3+ years of non-internship professional software development experience 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems Experience programming with at least one software programming language Fundamentals of machine learning models, their architecture, training and inference lifecycles along with work experience on some optimizations for improving model performance Preferred Qualifications
3+ 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 Hands-on experience with PyTorch or Jax, preferably involving developing and deploying LLMs in production on GPUs, Neuron, TPU or other AI acceleration hardware 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, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. 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 $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. Depending 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. Share this job
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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AWS Neuron is the complete software stack for the AWS Inferentia and Trainium cloud-scale machine-learning accelerators. This role is for a senior software engineer in the Machine Learning Inference Applications team. This role is responsible for development and performance optimization of core building blocks of LLM Inference - Attention, MLP, Quantization, Speculative Decoding, Mixture of Experts, etc. The team works side by side with chip architects, compiler engineers and runtime engineers to deliver performance and accuracy on Neuron devices across a range of models such as Llama 3.3 70B, 3.1 405B, DBRX, Mixtral, and so on. Responsibilities
Adapt latest research in LLM optimization to Neuron chips to extract best performance from both open source and internally developed models. Collaborate across teams and organizations to deliver optimized solutions for LLM inference on Neuron devices. Develop and optimize core building blocks of LLM inference, including Attention, MLP, Quantization, Speculative Decoding, and Mixture of Experts. About the team
Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge-sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects that help our team members develop your engineering expertise so you feel empowered to take on more complex tasks in the future. Basic Qualifications
3+ years of non-internship professional software development experience 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems Experience programming with at least one software programming language Fundamentals of machine learning models, their architecture, training and inference lifecycles along with work experience on some optimizations for improving model performance Preferred Qualifications
3+ 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 Hands-on experience with PyTorch or Jax, preferably involving developing and deploying LLMs in production on GPUs, Neuron, TPU or other AI acceleration hardware 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, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. 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 $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. Depending 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. Share this job
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