Amazon

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.

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.

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.

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.

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.

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.

Manager for an Applied Science team focused on extending Amazon Ads campaigns beyond the Amazon store using generative AI and machine learning to deliver sponsored experiences in third-party environments. The role involves leading scientists and engineers, shaping product direction, developing roadmaps, and driving advertiser outcomes through ML/GenAI solutions.

Senior Software Development Engineer role focused on building and scaling GenAI and ML solutions within the Amazon Music Catalog team. The role involves developing, deploying, and optimizing LLMs in production, working with distributed systems and data pipelines, and partnering with Applied Scientists and Product Managers to integrate AI-driven capabilities into catalog systems.

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.

Machine Learning Engineer at Amazon Ads focused on Sponsored Products and Brands, re-imagining advertising with generative AI. The role involves designing, coding, and supporting scalable ML pipelines and online serving systems, optimizing ML model performance and infrastructure, and implementing end-to-end solutions. It requires driving technical direction, building and growing teams, and collaborating on product direction. The team operates on a large product catalog with strict latency constraints and works with research scientists to deliver relevant ads.

This role focuses on building and deploying machine learning models for Amazon Devices Sales and Marketing, specifically for product recommendations, customer segmentation, and marketing initiative effectiveness. The candidate will own solutions end-to-end, from conceptualization to productionalization, and will collaborate with various teams to deliver customer-facing reporting tools and automated recommendation systems.

Software Engineer II role focused on deploying autonomous agents for supply chain optimization, leveraging generative AI and ML to build intelligent infrastructure. The role involves designing and deploying AI systems/agents, building Gen AI technologies with AWS, and collaborating with cross-functional teams.

Software Development Engineer role on the Data Center Gen AI team at AWS, focused on building generative AI solutions for data center operations. The role involves developing intelligent systems that optimize technician workflows, automate decision-making, and enhance operational efficiency using LLM integration, RAG, agent frameworks, and full-stack serverless technologies. The position aims to transform data center operations through AI/ML innovations and build platform primitives for other teams.

Partner Solutions Architect focused on Data and AI Go-To-Market (GTM) for Amazon QuickSuite, with a primary emphasis on designing and implementing enterprise BI solutions, AI-powered analytics platforms, and agentic AI systems for workplace automation. The role involves collaborating with partners and customers to adopt AWS services, devising engagement strategies, and providing architectural guidance for AI-driven business intelligence and autonomous workplace agents.

This role involves working with early-stage startups to help them leverage AWS technology for developing, training, tuning, and deploying generative AI foundation models. The focus is on architecting scalable, reliable, and secure solutions, supporting the adoption of AWS services, and providing feedback to product teams. The role also involves creating technical content and presenting at events.

This role involves working with early-stage startups to help them leverage AWS technology for developing, training, tuning, and deploying generative AI foundation models. The focus is on providing architectural guidance, supporting the adoption of AWS services, and acting as a technical advisor to help startups build scalable, reliable, and secure solutions.

This role focuses on enabling AWS partners to build, scale, and sell Generative AI solutions, specifically Foundation Models and Agentic solutions. The Solutions Architect will develop joint solutions, create go-to-market strategies, and drive technical enablement. Key responsibilities include architecting integrated solutions, building proof-of-concepts, influencing partner roadmaps, and creating technical content. The role requires deep technical expertise in GenAI, strong partner relationship management, and the ability to act as a technical liaison.

This role focuses on applying machine learning and GenAI to develop forecasting and optimization models for Amazon's physical retail presence, supporting real estate and network planning decisions. The scientist will design, implement, and own end-to-end ML solutions, including MLOps, and enhance user interaction with GenAI. The role involves analyzing large datasets, presenting findings to leadership, and collaborating with cross-functional teams.

Software Development Engineer role focused on building and optimizing low-latency, scalable connectivity services for Alexa devices. The role involves integrating AI-driven capabilities and AI-powered features into these services, as well as leveraging AI-augmented development tools to accelerate the software development lifecycle. The team operates at a massive scale, handling billions of transactions daily, and is increasingly adopting an AI-first approach.

Senior Software Development Engineer focused on acquiring, creating, and curating high-quality software engineering datasets for training Generative AI models, including Reinforcement Learning. The role involves designing and building automated systems for data mining and quality assessment, as well as developing GenAI-powered workflow tools to streamline data collection and assurance processes.

Software Development Engineer role focused on integrating Large Language Models (LLMs) into Alexa's audio experiences. The role involves designing and implementing software, creating infrastructure for LLMs in audio, developing tools to evaluate and improve model accuracy, reduce latency, and influence the operational roadmap for core audio services. The position also requires mentoring junior engineers and contributing to hiring efforts.

Software Development Engineer role focused on integrating Large Language Models (LLMs) into Alexa's audio experiences. The role involves designing and implementing software, creating infrastructure for LLMs in audio, developing tools to evaluate and improve model accuracy, reduce latency, and influence the operational roadmap for core audio services. The position also requires mentoring junior engineers and contributing to hiring efforts.

Software Development Engineer role focused on integrating Large Language Models (LLMs) into Alexa's audio experiences, aiming to improve model accuracy and reduce latency. The role involves designing and delivering software, creating infrastructure for LLMs, developing tools for evaluation, and influencing the operational roadmap for core audio services.

Software Development Engineer role focused on enhancing Alexa's audio experiences by integrating Large Language Models (LLMs), improving model accuracy, reducing latency, and building scalable API platforms. The role involves designing, implementing, and delivering software features, creating infrastructure for LLM integration, and influencing the operational excellence roadmap for audio services.