Amazon

Software Development Engineer role focused on applying Generative AI and LLMs to enhance Amazon Ads, improving ad retrieval, allocation, and recommendations for a personalized shopping experience. The role involves building large-scale distributed systems and data pipelines, collaborating with scientists and product managers, and driving operational excellence.

Software Development Manager for AWS Just Walk Out technology, focusing on building and enhancing the checkout-free shopping experience. The role involves managing a team of 6-10 engineers to deliver critical capabilities, leveraging vision, sensor fusion, and machine learning. The team builds the platform and architecture for retail capabilities, including order management and merchant integration.

Applied Scientist role focused on designing and building machine learning solutions for customer discovery of Amazon's Private Brands. The role involves end-to-end project management from ideation to launch, with a strong emphasis on causal ML, deep learning, and deploying models to production. The goal is to drive customer awareness and product discovery, impacting Amazon's own brands and contributing to broader discovery solutions across the company.

Applied Scientist II role at Amazon Ads focusing on Sponsored Products and Brands, specifically the Search Ranking and Interleaving (R&I) team. The role involves developing and applying GenAI and ML techniques to optimize ad ranking, allocation, and relevance on the search page. Key responsibilities include building real-time ML algorithms for ad auctions, developing multi-objective optimization methods, and researching new ML approaches to improve shopper experience and drive revenue. The role requires experience in building models for business applications and applying theoretical models in practice.

Software Development Engineer to architect and scale Gen AI-powered platforms and development tools that champion trustworthy customer experiences, privacy-by-design principles, and organizational trust at scale. This role will help set the standard for how privacy and trust technologies are implemented across D&S, driving end-to-end adoption of solutions that make trustworthy customer experiences the automatic choice for teams across Amazon.

The role involves applying deep learning, neural networks, and transformer architectures to price prediction and forecasting problems within Amazon's Pricing Optimization group. It focuses on developing and deploying ML models at scale to improve pricing and promotion strategies, requiring collaboration with product, engineering, and science teams.

Software Development Engineer focused on building and applying AI agents to simplify and accelerate customer adoption of AWS Neuron ML chips (Trainium and Inferentia). The role involves working with external and internal customers to identify obstacles and opportunities for accelerating adoption, and transforming service performance, durability, cost, and security.

Software Development Engineer focused on building and applying AI agents to simplify and accelerate customer adoption of AWS Neuron ML chips (Trainium and Inferentia). The role involves working with external and internal customers to identify obstacles and opportunities for accelerating adoption, and transforming service performance, durability, cost, and security.

The Principal Program Manager will lead Amazon's internal capability to understand, audit, and innovate within the agentic commerce paradigm, defining strategy and developing frameworks for autonomous, intent-driven commerce experiences. This role requires defining strategy, developing audit frameworks, conducting competitive analysis, and influencing senior leadership.

Manager for Navigation Science team at Amazon Prime Air, focusing on developing advanced navigation algorithms and flight software for delivery drones. Requires leadership experience, strong programming skills, and experience with agile development. The role involves defining system architectures, contributing to flight algorithms, and driving innovation in a safety-critical environment.

The Applied Scientist Intern will work on improving Amazon's product search service by designing and integrating machine learning models using TB-scale data. The role involves balancing business metrics and response times, and requires a PhD student in Computer Science, AI, ML, or related fields with experience in ML experiment design, statistical analysis, and coding.

Internship role focused on machine learning, deep learning, generative AI, LLMs, speech technology, robotics, computer vision, optimization, operations research, quantum computing, automated reasoning, or formal methods. The intern will own the design and development of end-to-end systems, write technical white papers, create roadmaps, and drive production-level projects. Collaboration with scientists and other interns is expected, with opportunities to design new algorithms and models.

Principal Product Manager, Technical for GenAI Evaluation Media (GEM) team at Amazon, focusing on visual shopping experiences, agentic AI, multi-modal personalization, and real-time image/video generation. The role involves defining product vision and roadmap, partnering with scientists and engineers, and driving data-informed decisions for customer-facing AI products.

Product leader to define and build the vision for AI-driven communication experiences for Alexa, focusing on generative AI transforming Alexa into a proactive, personal communications partner. The role involves owning end-to-end communication experiences across household, global, and AI-powered productivity, and pioneering real-time, multimodal AI primitives.

Software Development Engineer role focused on building a new Generative AI application (QuickSuite) for enterprises within AWS. The role involves translating requirements into deliverables, prototyping, designing, developing, and deploying scalable services, and mentoring junior engineers. It's an early-stage initiative with a focus on solving complex technical challenges in AI.

Machine Learning Engineer role focused on optimizing and tuning inference performance for AWS Neuron accelerators, specifically for large language models (LLMs) and other key ML model families. The role involves developing and performance tuning building blocks for the distributed inference library, ensuring high performance and efficiency on Trn2 and Trn3 servers. Requires experience with LLM inference optimization, kernels, Python, PyTorch, or JAX.

The role focuses on developing diverse datasets for training and evaluating AI models, using methods like synthetic data generation, model-supported generation, and human-in-the-loop collections. The Language Engineer will design data collections, create tasks, analyze data, build tools for data analysis/creation, and collaborate on AI model performance evaluation.

The role focuses on developing diverse datasets for training and evaluating AI models, utilizing synthetic data generation, model-supported generation, and human-in-the-loop approaches. Responsibilities include designing data collections, creating data using state-of-the-art methods, analyzing data, building tools for data analysis/creation, and collaborating on AI model performance evaluation.

Principal Engineer role at Amazon AWS Builder Acceleration focused on leveraging GenAI and advanced AWS technologies to simplify the software development, deployment, and maintenance lifecycle for AWS engineers. The role involves defining technical strategy, identifying high-impact problems, developing roadmaps, and pioneering AI-powered builder experiences at AWS scale.

Software Development Manager to lead an engineering team building generative and agentic AI-powered products and tools for Amazon Sellers and Account Managers, aiming to transform workflows and improve seller success.

The Language Engineer will develop diverse datasets for training and evaluating Amazon AI models, using synthetic data generation, model-supported generation, and human-in-the-loop methods. This role involves designing data collections, analyzing data, building tools for data creation, and collaborating with scientists and engineers to evaluate AI model performance. Experience with speech, text, and multimodal data is required.

The Language Engineer will develop diverse datasets for training and evaluating Amazon AI models, using synthetic data generation, model-supported generation, and human-in-the-loop methods. This role involves designing data collections, analyzing data, building tools for data creation, and collaborating with scientists and engineers to evaluate AI model performance. Experience with speech, text, and multimodal data is required.

This role is for a Senior SoC Power Engineer focused on developing and optimizing power consumption for machine learning accelerators (Inferentia and Trainium SoCs) within AWS. The engineer will be responsible for power analysis and modeling from RTL to netlist, identifying power saving opportunities, and correlating simulation results with lab measurements. This is an engineering role focused on the hardware infrastructure that powers AI workloads.

Software Development Engineer II role focused on building AI-native experiences for Alexa+ using generative AI and LLMs, empowering third-party partners to create engaging customer experiences. The role involves developing software for millions of devices, focusing on architecture, quality, and engineering best practices.

This role is for an AI Platform Builder, a Data Engineer focused on developing Platforms and Agentic AI solutions. The role involves designing, implementing, and maintaining data pipelines and platforms that power AI/ML initiatives, using AI for code generation, optimization, and building AI-native self-service data platforms. It emphasizes prompt-driven development and creating self-improving systems.

The Economist II, Featured Merchant Algorithm role at Amazon focuses on developing and deploying machine learning models that determine the 'Buy Box' offer and surrounding customer experience on Amazon's platforms. This involves ranking and selecting the best offer based on factors like price, availability, and delivery, impacting billions of transactions daily. The role requires a PhD in economics, strong data-driven decision-making, collaboration with cross-functional teams, and expertise in prediction and forecasting with large datasets.

This role focuses on building and deploying advanced machine learning models for consumer business applications, optimizing business operations and profitability. It involves end-to-end ownership from data analysis and model development to implementation and scaling, with a strong emphasis on creating automated processes for model lifecycle management.

Software Engineering Manager to lead a team focused on machine learning compiler design and development for AWS Neuron, driving optimization techniques, hardware bring-up, and influencing pre-silicon design decisions to accelerate ML infrastructure.

This role focuses on optimizing the performance of the AWS Neuron software stack, which supports Generative AI and ML workloads on AWS's custom ML accelerators (Inferentia and Trainium). The engineer will analyze ML workloads, develop high-performance kernels, enhance the Neuron SDK, and collaborate with compiler, frameworks, and hardware teams to maximize end-to-end performance. Responsibilities include instruction scheduling, memory management, parallelism, kernel optimization, and compiler enhancements, with a focus on ML inference and training performance.

Software Development Engineer role focused on building and delivering consumer-facing conversational assistant features using advanced LLM techniques like fine-tuning and prompt optimization for Alexa AI.

The role focuses on developing diverse datasets for training and evaluating AI models, utilizing synthetic data generation, model-supported generation, and human-in-the-loop approaches. Responsibilities include designing data collections, creating data with synthetic and model-based methods, analyzing data, building tools for data analysis/creation, and collaborating to evaluate AI model performance.

Postdoctoral Scientist role in Amazon Robotics focusing on computer vision and manipulation challenges in warehouses, involving developing robotic manipulators with machine learning approaches. The role requires innovation in 3D scene understanding and item identification for robotic interaction.

Sr. Manager of Applied Science with expertise in Statistical Machine Learning and/or Reinforcement Learning to drive research, development, and deployment of AI technology for supply chain optimization. The role involves managing a team of scientists, focusing on next-generation solutions for buying, placement, and fulfillment decisions, and translating customer needs into reusable software infrastructure. Key responsibilities include leading innovation in RL applications, building and developing a high-performing team, bridging technical possibilities with business requirements, and driving cross-functional collaboration.

This internship role focuses on applying data science and machine learning to solve complex problems in robotics at Amazon. Interns will design and implement solutions, research new algorithms, collaborate with experts, and build tools to improve robotics analytics and customer experience. The role involves working with various AI/ML fields including computer vision, LLMs, and deep learning within a robotics context.

Applied Scientist role focused on building machine learning models and technology to automatically monitor and classify billions of products in the Amazon catalog, ensuring compliance and safety. The role involves working with large datasets, deep learning for search matching and ranking, filtering, indexing, and document understanding, with a focus on delivering customer-facing experiences at Amazon scale.

The Machine Learning Compiler Engineer will work on the Amazon Neuron team to develop and scale a deep learning compiler stack for Amazon's custom ML accelerators (Inferentia and Trainium). This role involves optimizing neural network models for inference and training performance, integrating with ML frameworks, and contributing to the software stack that enables large-scale ML workloads. The engineer will be involved in pre-silicon design and bringing new features to market.

Senior Data Scientist at Amazon Pay to lead innovation in machine learning and artificial intelligence solutions, focusing on multi-agent systems and Generative AI applications. The role involves end-to-end ML project leadership, MLOps pipeline development, and deployment of ML solutions, with a secondary focus on inference infrastructure.

This role focuses on developing diverse datasets for training and evaluating AI models, utilizing synthetic data generation, model-based generation, and human-in-the-loop approaches. The Senior Language Engineer will define data creation strategies, lead complex data collections, and analyze large datasets. They will also build tools for data analysis and creation, and collaborate with scientists to evaluate AI model performance.

This role involves developing bare metal firmware for custom ASIC-based ML Accelerator chips, focusing on hardware/software co-design for machine learning acceleration systems. The engineer will work on the firmware that drives neural network model execution on custom silicon, collaborating with hardware design teams. While no prior ML knowledge is required, the role is core to enabling ML infrastructure.

The role focuses on building and maintaining a Spark-based infrastructure for processing large multimodal datasets critical for machine learning research, specifically for state-of-the-art agents within the AGI Autonomy organization. It involves data extraction, transformation, and creating tooling for researchers, with a secondary focus on agent development.

Master's student internship focused on applying machine learning, NLP, computer vision, automated reasoning, or robotics to design and develop end-to-end systems for Amazon Science. The role involves working with large datasets, implementing systems, and potentially deploying solutions into production.

Senior Applied Scientist role focused on developing and launching end-to-end AI solutions, specifically recommendation systems leveraging generative models, for Amazon's Sponsored Products and Brands advertising platform. The role involves defining science vision, designing experiments, and collaborating with engineering and product teams to improve advertiser and shopper experiences.

MS or PhD student internship in machine learning, deep learning, generative AI, LLMs, speech technology, robotics, computer vision, optimization, operations research, quantum computing, automated reasoning, or formal methods. Focus on designing and implementing state-of-the-art solutions for complex business problems, potentially leading to production-level projects and technical white papers. Collaboration with scientists and other interns is expected.

Senior Software Development Engineer role focused on building Gen AI native games and gameplay experiences, and enhancing internal team productivity through agentic solutions. The role involves architecting, developing, and operating infrastructure for proprietary and third-party models, building intelligent agents, and optimizing AI solutions for performance and cost. It also includes leading internal GenAI adoption and ensuring enterprise-grade security and responsible AI.

MS or PhD student internship in machine learning, deep learning, generative AI, LLMs, speech technology, robotics, computer vision, optimization, operations research, quantum computing, automated reasoning, or formal methods. Focus on designing and implementing state-of-the-art solutions for complex problems, potentially leading to production deployment and publication.

The Sr. Applied Scientist role in Amazon Logistics focuses on optimizing last-mile delivery operations through the development and application of machine learning models and algorithms. The role involves estimating costs, improving metrics, developing scalable processes, and working with technology teams to build new tools and systems that impact customer experience and delivery efficiency. It requires a PhD or equivalent experience in a quantitative field and strong analytical and program management skills.

MS or PhD student internship in machine learning, deep learning, generative AI, LLMs, speech, robotics, computer vision, optimization, operations research, quantum computing, automated reasoning, or formal methods. Focus on designing and developing end-to-end systems, writing technical white papers, creating roadmaps, and driving production-level projects. Opportunity to design new algorithms and models, potentially publish work at top-tier conferences.

MS student internship focused on building and deploying machine learning models for Amazon's business problems, with potential for worldwide scale. The role involves working with large datasets and cloud technology, and defining metrics for customer satisfaction.