Amazon

This role is for a Software Development Manager on the Agentic AI organization's Evaluations & Optimization team at AWS. The manager will lead a team of engineers to build systems for assessing the quality, performance, and reliability of GenAI and agentic systems, as well as optimization solutions. The work involves deep learning, distributed systems, and evaluation science, focusing on building infrastructure and tooling for evaluation workflows.

Software Development Engineer role focused on building intelligent, closed-loop decision systems for Amazon Robotics. This involves designing and building agentic AI systems that combine machine learning, real-time data processing, and LLM-driven reasoning to automate operational decision-making in robotic workflows. The role also includes developing end-to-end decision systems, scalable architectures on AWS, ML models, data pipelines, and implementing observability and evaluation frameworks. Collaboration with cross-functional teams and end-to-end ownership of production systems are key aspects.

Senior Software Engineer for Amazon Robotics Autonomous Mobility team, focusing on perception and localization software for warehouse robots. Responsibilities include developing ML capabilities, sensor fusion, SLAM, and optimizing performance. Requires strong software development and leadership experience, with preferred experience in robotics ML, C++, Python, ROS, and CUDA.

This role focuses on the end-to-end development and deployment of machine learning and data science solutions for intelligent communication experiences within Alexa. The Data Scientist will design, build, and improve ML models for capabilities like prioritization and intent detection, analyze large datasets, conduct experiments, and contribute to the applied science roadmap, ultimately delivering AI-driven solutions to millions of customers.

Manager of Data Science at AWS responsible for overseeing a team that builds large-scale distributed systems for abuse detection. The role involves defining business goals, aggregating data, managing research vision, mentoring scientists, and ensuring successful integration of AI models into production. Requires experience in managing data science teams, cross-functional projects, ML techniques, generative AI, foundation models, MLOps, and production deployment of AI systems.

Applied Scientist II role at Amazon Ads focused on building production ML and bandit solutions to customize the Sponsored Products search experience. The role involves determining ad placement, quantity, and targeting using machine learning, causal inference, and optimization techniques. It emphasizes improving shopper discovery and advertiser reach by modeling shopper responses and optimizing ad allocation and ranking on the search page, with a recent focus on integrating LLMs/GenAI for production use cases.

This role focuses on providing strategic oversight and mentorship for human-in-the-loop and model-in-the-loop data pipelines, ensuring data quality for LLM training and evaluations. The consultant will collaborate with AI teams, optimize data collection, and develop benchmarks for GenAI model performance.

Senior Software Engineer to lead a team building the operational backbone of a satellite laser communication network. The role involves architecting and delivering mission-critical tools and services for network operations, including systems that leverage machine learning and generative AI for anomaly detection, root cause analysis, and impact prediction. The engineer will also lead automation initiatives, collaborate with cross-functional teams, and mentor junior engineers.

Manager for a team working on LLM and/or VLM post-training and alignment for new personalized shopping experiences, leveraging customer behavioral data.

The Senior Applied Scientist will build AI-based services for Amazon Q Developer, focusing on redefining developer work. This role involves building AI agents and machine learning models, working closely with software engineers to deliver end-to-end modeling solutions, and driving discussions with customers and peers on modeling approaches. The work is expected to require scientific breakthroughs in ambiguous problem areas.

This role focuses on building causal predictive models that go beyond traditional forecasting, integrating modern machine learning techniques like LLMs and computer vision to understand and predict workforce outcomes. The scientist will write production-quality code for implementation into decision-making tools, bridging causal rigor with ML innovation.

This role focuses on the end-to-end development and deployment of machine learning and data science solutions for intelligent communication experiences within Alexa. The Data Scientist will design, build, and improve ML models for capabilities like prioritization and intent detection, analyze large datasets, conduct experiments, and contribute to the applied science roadmap, ultimately delivering AI-driven solutions to millions of customers.

Software Development Engineer role at Amazon Alexa Connections, focusing on integrating generative AI and machine learning into communication features to enhance customer experiences. The role involves designing and building scalable, fault-tolerant systems for AI/ML workloads, including Gen AI inference and training pipelines, within an agile environment.

Software Development Engineer II on the Customer Service Application Security team at Amazon. This role focuses on building innovative security solutions using Generative AI and LLMs to automate security processes, improve security posture, and increase developer productivity. The engineer will architect and develop native AWS solutions, including prompt engineering, security frameworks, and threat detection mechanisms, to create paved path solutions for developers.

This role is for a Security Engineering Manager within Amazon's AGI organization, focusing on securing Generative AI technologies. The manager will lead a team of security engineers and technical program managers to address novel security challenges like prompt injection, model poisoning, and data leakage. Key responsibilities include setting strategic direction for GenAI security processes, influencing stakeholders, developing team culture, and driving the adoption of GenAI-specific security practices and tooling. The role requires staying current with emerging GenAI security threats and mentoring team members.

Software Development Engineer role focused on designing, developing, and deploying full-stack robotic planning, tracking, and workcell solutions using AWS and AI-driven sortation optimization. The role involves building software for sortation at scale, improving safety, and optimizing package flow and fleet orchestration through ML-powered algorithms and intelligent systems.

Software Development Engineer role focused on building and operating the data platform infrastructure for an AI-driven analytics platform at AWS Identity. This involves designing and managing ingestion, transformation, and serving pipelines for petabyte-scale data to feed ML models and LLM agents. The role also includes productionizing ML models, building feature engineering infrastructure, and ensuring platform resilience and scalability.

This role leads strategic programs for Amazon Ads' AI infrastructure core services that accelerate agentic AI development. The TPM will define and execute the agentic AI core infra product roadmap, drive agent builder adoption, and ensure the core services scale to support multi-agent workflows and production-grade reliability for advertiser-facing and internal agents.

Manager for an Applied Scientist team focused on optimizing the returns and re-commerce process using ML, NLP, and Information Retrieval. The role involves managing scientists and engineers, developing ML models for business applications, and building scalable software systems.

Senior Applied Scientist role focused on developing AI-powered Discovery systems for AWS Marketplace, specializing in personalization, search, and recommendation systems. The role involves leading research, design, and development, translating scientific techniques into scalable solutions, and mentoring other scientists. It aims to accelerate cloud migrations and support partner growth.

This role focuses on delivering secure Generative AI solutions to enterprise customers, acting as both a security leader and hands-on practitioner. It involves conducting security assessments, architecting and implementing security controls for GenAI applications, and building reusable security patterns and accelerators. The role also involves developing innovative GenAI-powered security solutions and contributing to thought leadership.

Applied Scientist role at Amazon Prime Video focused on building machine learning systems for content presentation and discovery. The role involves working with multi-modal embeddings, contextualized ranking, reinforcement learning, and recommender systems to improve customer engagement with the Prime Video catalog.

Applied Scientist role focused on building and deploying end-to-end machine learning solutions to prevent eCommerce fraud and manage transaction safety within Amazon's production environment. The role involves innovating with GenAI/LLM/VLM technologies, analyzing large datasets, and creating automated risk evaluation and operational systems.

This role focuses on the operational excellence and reliability of a fleet of ML accelerators and server products, specifically Amazon's Trainium chips. The engineer will be responsible for debugging hardware and software issues, developing automation, analyzing fleet data, and ensuring the health and performance of the ML hardware infrastructure. This is an engineering role focused on the operational aspects of serving ML hardware.

Software Development Manager leading a team to build and deliver core infrastructure components for AI agents in Amazon Ads. This includes an agent-builder SDK, development tools, and a managed runtime, focusing on scalability, low-latency, and integration with Ads services and foundational models. The role bridges distributed systems, ML infrastructure, and developer tooling.

Applied Scientist role at Amazon Business Ads focusing on building and deploying scientifically novel software solutions for B2B advertising products. Requires experience in model building for business applications and proficiency in Python/deep learning frameworks.

Applied Science Manager for AGI team focusing on quality automation, auditing, and evaluation of LLMs and multimodal systems. Leads a team of scientists to develop quality strategies, auditing frameworks, and research new methodologies to ensure data integrity and model performance. Manages team development, cross-functional communication, and drives research into data impact and utility measurement for AI models.

Applied Scientist role focused on designing, developing, and deploying ML and computer vision models for Amazon's in-store grocery technologies, including smart carts, inventory intelligence, personalization, and store operations. The role involves end-to-end model development from ideation to production, with a focus on solving real-world problems at scale within the grocery domain.

This role focuses on designing and deploying agentic AI systems to automate complex workflows for fraud and abuse detection within Amazon's e-commerce platform. It involves advanced data analysis using SQL and Python, identifying risks, and scaling solutions across the business segment.

Software Development Engineer role focused on building AI/ML-powered products and infrastructure for data integration workflows at Amazon.

This role is for a Senior Applied Science Manager on the Stores Economics and Science team at Amazon. The team uses economics, statistics, and machine learning to understand and design Amazon's buyer and seller economy. The manager will provide structure for complex business problems, work with ML scientists to validate models, and help partners translate analysis into impactful actions. The role requires experience in building large-scale ML/AI solutions, leading scientists, and developing junior talent.

The Applied Scientist will leverage LLMs and generative AI to build automated solutions for seller verification, transaction monitoring, and risk assessment in Amazon's marketplace. The role involves designing, developing, and deploying end-to-end ML solutions to detect and prevent abuse patterns, requiring innovation with the latest GenAI technology and adaptation to evolving threats.

The Language Engineer will develop diverse datasets for training and evaluating Amazon's AI models, utilizing synthetic data generation, model-supported generation, and human-in-the-loop approaches. This role involves designing data collections, analyzing data, building tools for data analysis/creation, and collaborating with scientists and engineers to evaluate AI model performance. Experience with multimodal data and agentic workflows is preferred.

Language Engineer role focused on dataset construction, linguistic annotation, dialog/semantic schemas, and automatic processing of large datasets for AGI Data Services. The role involves designing data collection tasks, analyzing data for insights, building data authoring tools, and collaborating with scientists to evaluate language models.

The Language Engineer will develop diverse datasets for training and evaluating Amazon's AI models, utilizing synthetic data generation, model-supported generation, and human-in-the-loop approaches. This role involves designing data collections, analyzing data, building tools for data analysis/creation, and collaborating with scientists and engineers to evaluate AI model performance. Experience with multimodal data and agentic workflows is preferred.

The Language Engineer will develop diverse datasets for training and evaluating Amazon's AI models, utilizing synthetic data generation, model-supported generation, and human-in-the-loop approaches. This role involves designing data collections, analyzing data, building tools for data analysis/creation, and collaborating with scientists and engineers to evaluate AI model performance. Experience with multimodal data and agentic workflows is preferred.

Machine Learning Engineer focused on developing and deploying ML products for network management within Amazon Infrastructure Engineering, aiming to improve customer experience and revolutionize business operations.

Senior Applied Scientist role focused on leveraging generative AI and machine learning to re-imagine advertising experiences for Amazon Ads' Sponsored Products and Brands. The role involves leading ML efforts, analyzing large datasets, building and deploying ML models for insights, traffic monetization, and personalized shopping experiences, and driving end-to-end ML projects. It also includes running A/B experiments, establishing scalable processes, researching new ML approaches, and recruiting/mentoring other scientists.

Applied Scientist II role at Amazon Ads focused on building production ML and bandit solutions to customize the Sponsored Products search experience. The role involves determining ad placement, quantity, and targeting using machine learning, causal inference, and optimization techniques. It emphasizes improving shopper discovery and advertiser reach by modeling shopper responses and optimizing ad allocation and ranking on the search page, with a recent focus on integrating LLMs/GenAI for production use cases.

Senior Robotics Engineer role focused on designing, deploying, and managing advanced robotic systems at scale within AWS data centers. This involves developing robust robotic solutions, collaborating with external partners, and ensuring reliability, efficiency, and scalability. The role requires experience with vision language actuation models and shipping production code.

This role focuses on designing and implementing enterprise-scale Generative AI solutions using AWS services, optimizing performance, and guiding teams in integration. It involves a mix of technical implementation and strategic guidance for AI applications.

The Data Scientist, Digital Acceleration role at Amazon focuses on designing and delivering advanced analytics and machine learning models for Amazon's digital businesses. The role involves end-to-end project management, from ideation to deployment, with a strong emphasis on Generative AI solutions and LLMs to enhance data access and solve customer problems within the Digital Acceleration Analytics team.

Senior Software Development Engineer to build and optimize infrastructure for AI/ML workloads on EC2 Nitro. Focus on performance measurement, benchmarking, regression testing, and influencing future hardware designs for LLMs, multimodal systems, and emerging architectures. Role involves both customer-facing performance problem-solving and foundational infrastructure development.

Software Development Engineer to build and optimize performance measurement infrastructure for AI/ML workloads on AWS EC2 Nitro. The role involves low-level systems, ML frameworks, and serving layers to translate performance insights into technical requirements for platform designs.

Software Development Engineer to build and optimize performance measurement infrastructure for AI/ML workloads on AWS EC2 Nitro. The role involves low-level systems, ML frameworks, and serving layers to translate performance insights into technical requirements for platform designs.

The Language Engineer will develop diverse datasets for training and evaluating Amazon's AI models, utilizing synthetic data generation, model-supported generation, and human-in-the-loop approaches. This role involves designing data collections, analyzing data, building tools for data analysis/creation, and collaborating with scientists and engineers to evaluate AI model performance. Experience with multimodal data and agentic workflows is preferred.

Applied Scientist role focused on developing and launching AI solutions for Prime Video's search and personalization systems, involving deep learning, GenAI, and reinforcement learning. The role requires end-to-end ownership from design to launch, including experimentation and evaluation, with a strong emphasis on delivering customer-facing products. Research publication is also a component.

The Applied Scientist will lead Machine Learning efforts for Amazon Ads' Demand Forecasting & Guidance team. This role involves hands-on analysis and modeling of large datasets to develop insights, build and deploy ML models into production, and run A/B experiments. The goal is to create best-in-class forecasting products for advertisers to predict campaign outcomes and optimize ad performance, directly impacting key business decisions.