Amazon

Software Development Engineer focused on optimizing and enabling AI/ML model inference on AWS's custom hardware accelerators (Inferentia and Trainium), working across the stack from frameworks like PyTorch/JAX to hardware-specific optimizations and kernel development.

Senior Manager role leading a team of Applied Scientists and Engineers to develop and deploy generative AI solutions for Amazon's Sponsored Products and Brands advertising platform, focusing on multi-lingual and multi-modal applications to drive growth in non-US markets.

Machine Learning Systems Engineer for Frontier AI Robotics team, focusing on building and optimizing distributed training infrastructure for large-scale deep learning and transformer models. Role involves engineering scalable, high-performance systems for AI research and applications, with a focus on robotics, multimodal perception, and manipulation strategies. Requires strong software development, ML infrastructure, and deep learning framework expertise.

AI Platform Data Engineer responsible for designing, building, and maintaining data pipelines, curated datasets for AI/ML consumption, and AI-native self-service data platforms using an AI-first development methodology. The role emphasizes leveraging AI at every layer of the data stack, including using AI agents for code optimization, building AI-powered platforms for AI models, and deploying intelligent agents for data accessibility. Experience with Gen AI enhanced development pipelines, agentic workflows, and prompt engineering is mandatory.

The RBKS AI team at Amazon is seeking Applied Scientists to innovate AI features for Ring and Blink cameras, focusing on the intersection of computer vision, generative AI, and ambient intelligence. The role involves productizing research into advanced computer vision and multimodal GenAI models for video understanding, object detection, and real-time applications, with an emphasis on privacy-preserving, efficient fine-tuning, and on-device/in-cloud inference. The goal is to ship AI solutions that enhance home security for millions of customers.

Lead a team to invent and build the SPB-Agent, a GenAI platform transforming retail-media advertising for Amazon advertisers. This agent will act as an intelligent advisor integrated into Amazon Ad Console and Seller/Vendor portals, using conversational interfaces and deep reasoning to help advertisers discover growth opportunities, optimize campaigns, and execute strategies at scale.

This role focuses on designing and deploying GenAI, NLP, and Computer Vision solutions to enhance customer experience and automate operations within Amazon's retail business. It involves developing novel ML models for task automation, text and image processing, and anomaly detection, with a strong emphasis on multi-modal LLM agents and retrieval systems.

Senior Software Engineer role focused on optimizing and deploying large AI models (LLMs, vision generative AI) on AWS's custom AI accelerators (Inferentia, Trainium). The role involves architecting distributed inference solutions, optimizing performance from high-level frameworks to hardware implementations, and developing tools for LLM accuracy and efficiency. It bridges ML frameworks (PyTorch, JAX) with AI hardware, focusing on inference performance and scaling.

This role focuses on optimizing and fine-tuning Generative AI models for edge platforms, working closely with custom ML hardware. The scientist will train custom models, analyze deep learning workloads, and collaborate with cross-functional teams to build ML-centric solutions for consumer devices. The role also involves publishing research and presenting at ML conferences.

Applied Scientist II role focused on developing and deploying sophisticated AI solutions for Amazon's Strategic Account Services (SAS) organization, leveraging deep learning, LLMs, and advanced ML techniques to improve seller operations and internal consultancy. The role involves end-to-end development from research to production, including architecting recommendation and optimization systems, pioneering applications of foundation models, and conducting rigorous A/B experiments.

This role leads the development of generative AI applications for advertisers, focusing on agentic experiences for recommendations and guidance. It involves fine-tuning, reinforcement learning, and preference optimization, with a strong emphasis on creating customer-facing products and mentoring AI talent.

Software Engineer role focused on building and tuning distributed training solutions for AWS Inferentia and Trainium accelerators, specifically for large language models and other ML model families. The role involves working with PyTorch, Jax, XLA, and the Neuron compiler/runtime to maximize performance and efficiency on AWS Trainium.

Senior Software Development Engineer focused on ML Data Infrastructure for Frontier AI Robotics at Amazon. The role involves building and maintaining scalable data infrastructure, designing dataset management systems, developing visualization tools, and implementing advanced data filtering techniques to support cutting-edge AI robotics research. Collaboration with science teams is key, requiring both infrastructure development and hands-on technical contribution to data preparation.

Senior Software Development Engineer role focused on optimizing and enabling AI/ML model inference on AWS's custom hardware accelerators (Inferentia and Trainium) through the Neuron SDK. The role involves system-level optimizations, performance tuning for latency and throughput, building infrastructure for model onboarding, and collaborating across hardware, software, and framework teams to ensure optimal performance for customers running large language models and other GenAI workloads.

Software Development Engineer to lead and architect next-generation model serving infrastructure for generative AI applications on AWS Inferentia and Trainium accelerators, focusing on performance, reliability, and scalability of inference serving systems.

Senior Applied Scientist role focused on developing and deploying machine learning models for Amazon's autonomous delivery systems, specifically in perception, prediction, and decision-making for autonomous vehicles. The role involves designing algorithms, leading research, transforming concepts into production, creating evaluation frameworks, and collaborating with engineering teams.

The Annapurna Labs team at AWS is seeking an Engineering Manager to lead a team focused on optimizing ML kernel performance for AWS Neuron, their custom ML accelerators (Inferentia and Trainium). The role involves designing and implementing high-performance kernels, optimizing compiler and runtime performance, and working closely with customers to enable their ML models. This position operates at the hardware-software boundary, combining deep hardware knowledge with ML expertise to accelerate deep learning and GenAI workloads.

Software Development Engineer focused on optimizing and enabling AI/ML model inference on AWS's custom hardware accelerators (Inferentia and Trainium), working across the stack from frameworks like PyTorch/JAX to hardware-specific optimizations and kernel development.

Software Engineer II role focused on optimizing LLM inference performance on AWS custom ML accelerators (Inferentia and Trainium) using the AWS Neuron SDK. This involves developing and tuning ML models and frameworks, building infrastructure for model onboarding, implementing low-level optimizations, and collaborating across hardware, software, and ML teams to ensure peak performance for customers.

Senior Software Development Engineer role focused on optimizing and enabling AI/ML model inference on AWS's custom hardware accelerators (Inferentia and Trainium). The role involves working across the stack from frameworks (PyTorch, JAX) to hardware, building infrastructure, optimizing performance (latency and throughput), and collaborating with various teams and customers to ensure efficient execution of large language models and other GenAI workloads. Experience with inference serving platforms like vLLM is required.

Seeking a Simulation Engineer to join an AI robotics research team, focusing on developing 3D physics-based simulation frameworks and tools to enable large-scale machine learning model training for robotics. The role involves developing simulations for reinforcement learning, closed-loop simulations, synthetic data generation, implementing robotics features, building real-to-sim workflows, and collaborating with ML researchers.

Principal Applied Scientist role focused on building industry-leading Conversational AI Systems using Generative AI, LLMs, NLU, Dialog Systems, and Applied ML. The role involves developing novel algorithms and modeling techniques to advance human language technology, impacting millions of customers through products and services. It requires a PhD, extensive experience in ML model building for business applications, and a strong publication/patent record. The team uses generative AI and foundation models to reimagine customer experiences on AWS.

Senior Software Engineer focused on performance optimization for distributed AI model training on AWS Trainium accelerators. The role involves working with frameworks like PyTorch and JAX, optimizing the Neuron software stack, and improving training throughput and efficiency for large-scale models.

The role focuses on optimizing ML kernel performance for AWS Neuron SDK on custom ML accelerators (Inferentia and Trainium). It involves designing and implementing high-performance compute kernels, analyzing and optimizing kernel-level performance, implementing compiler optimizations, and collaborating with customers and internal teams to enable and optimize ML models. The work is at the hardware-software boundary, combining deep hardware knowledge with ML expertise.

Data Scientist II role focused on applying statistical, machine learning, and GenAI methodologies to enhance employee experience within Amazon's People Experience and Technology organization. The role involves designing, developing, and maintaining scalable models and prototypes, partnering with cross-functional teams, and creating benchmarks for GenAI model performance.

Data Scientist II role focused on applying statistical, machine learning, or GenAI methodologies to enhance employee experience within Amazon's People Experience and Technology organization. The role involves designing, developing, and maintaining scalable models and prototypes, partnering with cross-functional teams, and communicating results to diverse audiences.

Applied Scientist role focused on developing and deploying optimization, simulation, and machine learning solutions for Amazon's Fulfillment Network. The role involves understanding operational processes, developing mathematical models, creating prototypes, partnering with engineers for production integration, and designing experiments to test solutions. The team has expertise in operations research, optimization, scheduling, planning, simulation, and machine learning.

Applied Scientist role focused on developing and optimizing delivery capacity in Amazon's Last Mile network. Requires strong skills in Operations Research or Machine Learning, building ML models, developing algorithms for business applications, and optimizing system policies. The role involves turning business requirements into mathematical models, contributing to production systems, and analyzing data.

This role focuses on designing, developing, and evaluating innovative optimization and machine learning models for Amazon's outbound transportation planning and execution systems. The scientist will work with large-scale data and distributed computing on the cloud to optimize inventory and shipments, reduce transportation costs, and improve customer experience. Collaboration with product managers and software engineers is key to building and integrating these solutions into production systems.

Software Development Engineer role focused on building AI systems for Amazon's Shopping Personalization. The role involves designing and implementing features that use generative AI and LLMs to personalize product discovery and recommendations for customers at Amazon scale. Emphasis on end-to-end ownership, scalability, reliability, and collaboration with product and science teams.

Delivery Consultant for AWS Professional Services focused on AI/ML and GenAI solutions in the Healthcare and Life Sciences sector. Responsibilities include end-to-end project implementation, designing ML pipelines and MLOps, collaborating with cross-functional teams, and advising customers on AI/ML strategies using AWS services.

AWS Professional Services is seeking an AI/ML Architect to help Canadian Public Sector clients adopt and implement ML and Generative AI solutions. The role involves understanding business challenges, designing and building ML/GenAI solutions using AWS services, and collaborating with engineering teams to bring them to production.

This role is for a Delivery Consultant on the AWS Professional Services team, focusing on designing, implementing, and managing AI/ML and Generative AI solutions for enterprise customers. The consultant will work with customers to understand business needs, prepare data, develop and deploy models, and ensure solutions are scalable, secure, and performant using AWS services and MLOps best practices. The role involves acting as a trusted advisor, collaborating with cross-functional teams, and sharing knowledge.

ML Engineer role focused on building and deploying AI/ML products for Amazon Tablets, specifically enhancing customer engagement through personalized recommendations and content ranking. The role involves end-to-end ML pipeline development, MLOps, and leveraging deep learning, LLMs, and generative AI for on-device experiences. It emphasizes shipping customer-facing ML solutions at Amazon scale.

This role is for a Partner Solutions Architect focused on driving innovation for SAP on AWS, with a strong emphasis on generative AI and agentic systems. The individual will architect and deliver solutions, proofs of concept, and reference architectures, combining AWS services with SAP technologies. They will leverage deep AI/ML and SAP functional expertise to solve complex customer problems and build partner capabilities. The role involves engaging with C-suite executives and technical practitioners to drive business-value-led conversations and influence the AWS product roadmap.

Applied Scientist role focused on developing and optimizing delivery capacity in Amazon's Last Mile network. Requires strong skills in Operations Research or Machine Learning, building ML models, developing algorithms for business applications, and optimizing system policies. The role involves turning business requirements into mathematical models, contributing to production systems, and analyzing data.

Senior Technical Program Manager to drive organizational effectiveness through hands-on development of AI-powered tools, automation, and knowledge systems for the Field Engineering team within AWS Infrastructure Services. The role focuses on leveraging generative AI technologies, including Amazon QuickSight, to streamline processes, enhance engineering analysis, and accelerate availability solutions.

Senior Solutions Architect focused on helping GovTech ISVs build and scale generative AI and agentic systems on AWS, with a strong emphasis on regulated environments. The role involves guiding technical strategy, architecture, and productionization of AI prototypes into robust, scalable applications.

Senior Solutions Architect for GovTech ISVs, focusing on helping them build and scale generative AI and agentic systems on AWS. The role involves guiding technical strategy, architecture, and security for regulated environments, with an emphasis on modernizing platforms and ensuring AI solutions are production-ready.

Software Development Engineer role focused on building applied AI solutions, specifically agentic products, within the AWS Applied AI Solutions organization. The role involves transforming research into production systems, owning end-to-end deployment of Generative AI and ML methods, and establishing scalable processes for ML development and serving.

This role is for an AI Specialist Solutions Architect (SSA) at AWS, focusing on helping enterprise customers adopt and scale GenAI/ML and Agentic technologies. The role involves building technical relationships, advising on architectures, and advocating for customer needs to influence AWS roadmaps. It requires a strong understanding of production software and LLM deployment, with a focus on translating AI ambitions into scalable, operational programs.

Software Development Engineer (MLE) for the CreativeX RAPID team at Amazon, focusing on real-time ad personalization and insights. The role involves tailoring visual ad experiences using technologies like latent diffusion models, LLMs, RL, and computer vision to provide dynamically optimized creatives with low latencies. Responsibilities include investigating new generative AI technologies, prototyping, evaluating feasibility, building data pipelines, and developing platforms for ML model deployment.

Software Development Engineer role focused on building and optimizing AI-powered personalization and recommendation systems for Prime Video's Linear TV segment. The role involves designing and implementing high-performance personalization systems, productionizing ML models with Applied Scientists, architecting data pipelines, developing real-time serving infrastructure, and leading A/B testing frameworks. Requires strong software development skills, experience with ML frameworks, SQL, distributed systems, and knowledge of recommendation systems and model serving.

Senior ProServe Cloud Architect for Healthcare and Life Sciences at AWS, focusing on designing and implementing AI and cloud solutions for pharmaceutical customers. This role involves understanding customer business objectives, architecting scalable AWS solutions for clinical development challenges, and advising on emerging technologies including agentic AI applications. The position requires deep domain knowledge of the pharmaceutical sector, including data standards and compliance frameworks, and collaboration with various AWS teams to drive innovation and customer success.

Senior Delivery Consultant for AWS Professional Services, focusing on designing, implementing, and managing GenAI and ML solutions for customers. The role involves technical guidance, collaboration with stakeholders, and advising on AI/ML trends and technologies, with a strong emphasis on AWS services.

Machine Learning Engineer II at Amazon, focusing on Search Engine Technologies and Document Retrieval within the consumer domain. The role involves applying ML models to improve customer experiences in the online retail search application, processing large datasets, and integrating models into production systems at scale.

Machine Learning Engineer II at Amazon, focusing on Search Engine Technologies and Document Retrieval within the consumer domain. The role involves applying ML models to improve customer experiences in the online retail search application, processing large datasets, and integrating models into production systems at scale.

The Machine Learning Compiler Engineer II on the AWS Neuron team will support the development and scaling of a compiler for AWS Machine Learning accelerators (Inferentia and Trainium chips). This role involves architecting and implementing features for the AWS Neuron Software Development Kit (SDK), which optimizes neural network models for custom AWS hardware. The engineer will work with ML frameworks like PyTorch and TensorFlow, contributing to a toolchain aimed at improving ML performance.