Amazon

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.

Data Scientist II on the Alexa Smart Home team to develop machine learning models, analytical frameworks, and Gen-AI powered solutions that improve product quality, inform strategic decisions, and enable proactive detection of customer experience issues. This role involves working with large-scale behavioral and interaction datasets, designing experimentation frameworks, and partnering with engineering, product, and science teams to deliver data-driven solutions.

Applied Scientist role focused on developing and optimizing Visual Inertial Odometry (VIO) and sensor fusion systems for intelligent robots, involving algorithm development, embedded deployment, and leveraging ML for perception. The role requires hands-on experience with sensors, hardware, and real-world data, with a focus on real-time performance on resource-constrained robotic platforms.

This role focuses on building and evaluating state-of-the-art ML models for biology and life sciences applications, requiring experience with deep learning methods and programming in languages like Python. The role is part of a special projects team aiming to innovate at scale and bring products to market.

Software Development Engineer II role focused on building an AI-native framework for customer experience engineering within Amazon Prime. The role involves designing and developing Agentcore infrastructure, multi-agent orchestration, and autonomous experimentation capabilities, aiming to compress CX development from weeks to hours using GenAI.

Senior AI/ML Architect role within AWS Professional Services, focusing on building and deploying ML and Generative AI solutions for Canadian Public Sector clients. This involves understanding business needs, designing solutions using AWS ML services, collaborating with engineering teams, and supporting projects from inception to production.

Software Development Manager leading a team to build AI-powered customer support products for Amazon Advertising, focusing on AI agents and automation for advertiser case resolution and campaign management.

Software Development Engineer role focused on building AI/ML-powered products and infrastructure for data integration workflows within Amazon's AWS Utility Computing organization. The role involves designing, developing, and optimizing AI/ML systems, collaborating with data scientists, and contributing to the full software development lifecycle.

Software Development Manager for GenAI Evaluation Media (GEM) team at Amazon, focusing on visual shopping experiences. The role involves leading a team to drive technical vision and execution of AI capabilities for generating and governing billions of visual assets at scale, ensuring quality and trustworthiness for customer purchase decisions. Requires strong technical expertise, business acumen, and leadership skills to partner with stakeholders, drive innovation, and maintain operational excellence.

Software Development Engineer role in Amazon's Finance Technology group, focusing on building big data and ML systems for fraud detection using Generative AI and LLMs. The role involves developing ML pipelines to process large transaction volumes and collaborating with scientists and finance teams.

Senior Technical Product Manager for advanced robotics systems, focusing on AI, control systems, and mechanical design for automation at scale. Requires deep robotics engineering expertise, including motion planning, control systems, computer vision, and machine learning, with experience in ROS, real-time OS, and embedded systems. Role involves translating technical requirements into roadmaps, evaluating tradeoffs, and driving product strategy for robotic manipulation, locomotion, and human-robot interaction.

Senior Specialist Solutions Architect for AI at AWS Mexico, focusing on architecting enterprise-grade AI/ML and generative AI solutions for C-suite executives. Requires deep technical experience in ML, GenAI, and agentic capabilities, including LLM customization, fine-tuning, inference optimization, agentic frameworks, RAG, and prompt engineering, with a focus on delivering measurable business outcomes and adhering to governance and compliance standards.

Software Development Engineer role focused on building solutions for Sponsored Products and Brands, utilizing generative AI, machine learning, and high-scale low-latency systems to improve customer experiences off the Amazon store. The role involves designing and developing components, big data systems, and ML-based approaches in collaboration with scientists and economists.

Software Development Engineer role focused on building and managing Agentic AI capabilities for AWS analytics services, specifically an Apache Spark Upgrade Agent that uses conversational interfaces and automated code transformation to reduce upgrade timelines. The role also involves managing a Model Context Protocol server for AI assistants and Agents, providing secure access to troubleshooting and code recommendation tools.

This Data Scientist II role focuses on building scientific tooling for how business customers interact with Long-Term Planning and Forecasting (LTPF) forecasts and plans. The role involves developing causal inference models, automated explainability frameworks, and variance bridging methodologies. It also includes building GenAI-powered narrative generation capabilities and automated hypothesis ranking to synthesize quantitative variance outputs into human-readable performance summaries and identify drivers of forecast error. The position emphasizes leading cross-functional programs, defining multi-year strategy, and leveraging insights for strategic decision-making.

This role focuses on developing causal inference models, automated explainability frameworks, and GenAI-powered narrative generation to translate forecasting outputs into actionable business intelligence for Amazon's business customers. The data scientist will build automated variance decomposition models and a causal model library with standardized pipelines, applying techniques from causal inference and time-series econometrics.

Applied Scientist II role focused on developing and deploying machine learning models and data-driven solutions for operational efficiency in Amazon's Fulfillment Centers and Transportation Sites. The role involves working with diverse datasets and ML frameworks to create predictive models, optimization algorithms, and intelligent automation, with a focus on scalability and production readiness. The team specifically handles network device management through a user-friendly, auditable mechanism for provisioning, configuration, and policy management.

This role focuses on applying advanced automated reasoning techniques, including SAT, SMT, symbolic simulation, and program analysis, to solve complex problems within AWS. The goal is to enhance privacy and sovereignty for AWS services, impacting business and customer outcomes through scientific innovation and strategic problem-solving.

Applied Scientist role focused on automated reasoning, privacy, and sovereignty within AWS. Requires a Ph.D. and experience in areas like SAT, SMT, symbolic simulation, and program analysis. The role involves solving complex problems, designing and implementing solutions, and providing technical influence across organizations.

Applied Scientist role focused on automated reasoning, privacy, and sovereignty within AWS. The role involves solving complex problems, designing and implementing solutions, and providing cross-organizational technical influence. Requires a PhD or Master's with significant applied research experience in areas like SAT, SMT, theorem proving, symbolic simulation, program analysis, or type systems. Experience with specific programming languages like O'Caml, Dafny, Haskell, Lean, or Rust is preferred.

The Applied Scientist role in AWS Automated Reasoning focuses on developing advanced solutions for automated reasoning, privacy, and sovereignty within AWS. This involves solving complex problems, designing and implementing solutions with long-term impact, and providing cross-organizational technical influence. The role requires deep knowledge in areas like SAT, SMT, mechanical theorem proving, symbolic simulation, and program analysis, with a Ph.D. and 4+ years of applied research experience.

Applied Scientist role focused on automated reasoning, privacy, and sovereignty within AWS. Requires a PhD and experience in areas like SAT, SMT, theorem proving, or program analysis. The role involves solving complex problems, designing and implementing solutions, and providing cross-organizational technical influence.

Applied Scientist role at Amazon Ads focusing on generative AI for sponsored products and brands. The role involves developing and researching real-time ML algorithms for ad auctions and multi-objective optimization, aiming to improve customer experience and drive revenue. It requires end-to-end ML project ownership in a highly ambiguous and large-scale environment.

Applied Scientist role focused on building causal ML systems for Amazon's pricing decisions. The role emphasizes shipping production-quality pipelines with real business impact, bridging econometric analysis and ML pipelines. Responsibilities include designing, training, and deploying causal estimation models, owning causal ML methodology, supporting pricing experiment analysis, and connecting model outputs to business outcomes.

This role focuses on implementing end-to-end AI/ML and GenAI solutions for enterprise customers using AWS services. The consultant will design, deploy, and manage these solutions, focusing on MLOps and customer success throughout the project lifecycle.

Senior Delivery Consultant for AWS Professional Services focused on designing, implementing, and managing AI/ML and Generative AI solutions for enterprise customers. This role involves leading project teams, hands-on development, MLOps, and advising customers on cloud AI/ML architectures using AWS services.

Software Development Engineer role focused on building AI-powered planning infrastructure for Amazon Ads. The role involves designing and delivering agentic skills, multi-step orchestration workflows, scalable APIs, and ML-informed optimization services. The tech stack includes TypeScript, Python, and AWS services.

Economist II role focused on causal inference and machine learning for Prime Video Ads, involving experiment design, model building, and translating findings into business decisions. Requires a quantitative approach and end-to-end model implementation.

AI Engineer role focused on deploying and productizing agentic AI models for automation at scale within Amazon Business EU. Responsibilities include developing AI agents, owning end-to-end deployment, establishing scalable ML processes, and contributing to customer-facing features.

Data Scientist II role focused on building LLM-powered financial forecasting and knowledge retrieval systems, including RAG, for Amazon's WW Ops FP&A team. Requires translating business ambiguity into production-grade AI solutions and influencing roadmaps.

This role is for a Senior Delivery Consultant focused on AI/ML solutions within AWS Professional Services. The consultant will design, implement, and manage AWS-based AI/ML applications and models for customers, providing technical guidance and support throughout the project lifecycle. Key responsibilities include gathering requirements, proposing model training and deployment strategies, and acting as a trusted advisor on AI/ML trends. The role requires experience with AWS AI/ML services and deploying LLMs in production.

Senior Product Manager to lead product strategy for cargo security and risk prevention within Amazon's global logistics network. The role involves building new products and evolving existing roadmaps to protect inventory, utilizing machine learning for real-time monitoring and predictive risk detection. This position requires defining product vision, driving cross-functional execution with engineering and data science, and scaling ML-powered solutions into production.

Senior Systems Development Engineer role focused on developing AI/ML systems, autonomous robotics, and agentic workflow automation for facility design and deployment within Amazon's global fulfillment network. The role involves identifying and implementing technical solutions, developing internal tooling, contributing to product roadmaps, and mentoring engineers, with a strong emphasis on AI and innovation.

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.

Senior Applied Scientist role focused on building and deploying large-scale machine learning systems for fraud and risk prevention in an e-commerce environment. The role involves leading scientific strategy, defining roadmaps, designing and deploying ML solutions, and leveraging GenAI/LLM technologies. It requires experience in real-time production environments, ML modeling, and translating scientific trends into production solutions.

Software Development Manager for Amazon Leo AI Foundations, responsible for designing, implementing, and operating globally distributed systems for a low Earth orbit satellite network. The role focuses on building near real-time analytics, a data lakehouse, and supporting agentic AI capabilities, including architecting a vector database with sub-100ms retrieval times and hybrid search strategies. The team builds the intelligent cloud backbone for AI-driven decision making across the Leo constellation, optimizing network performance and user experience.

Manager for a Data Science team focused on optimizing outbound communications for millions of customers using AI/ML, including LLMs and RL. The role involves leading the development of personalized messaging strategies, designing experiments, building propensity models, driving AI transformation in data accuracy and reporting, and owning financial planning frameworks. It also includes hiring, mentoring, and cross-functional partnership.

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 on the Sponsored Products and Brands Off-Search team, focused on building hyper-scale systems and data pipelines leveraging Generative AI and LLMs to improve advertising and shopping experiences. The role involves designing and delivering scalable solutions for ad retrieval, allocation, and recommendations, transforming these into personalized and contextually aware parts of the customer journey.

This role focuses on building AI-powered analytics experiences, specifically conversational agents and prompt-driven interfaces using LLMs and generative AI, to provide proactive insights for Amazon's advertising supported publishers. The engineer will own the end-to-end insight lifecycle, from data modeling to executive recommendations, and mentor other engineers.

Software Development Engineer III on the Amazon Private Brands (APB) team, responsible for building and evolving the core platform capabilities for a shared data, workflow, and AI agent platform. This includes dynamic data management, task orchestration, and AI agent infrastructure built on Amazon Bedrock. The role involves full-stack development, influencing technical direction, and partnering with consuming teams to ensure platform scalability. The engineer will own and operate backend services, lead technical roadmap, drive architecture decisions, mentor junior engineers, and translate business requirements into technical solutions.

Applied Scientist II role focused on developing and implementing machine learning and causal inference models for Amazon's advertising incrementality measurement. The role involves end-to-end model development, improving existing solutions, and collaborating with product and engineering teams to bring solutions to production. The team builds scientifically-rigorous causal inference methodologies at scale to help customers understand the impact of advertising.

Applied Scientist role at Amazon Ads focused on developing and productionizing end-to-end measurement solutions using Generative AI, classical ML, Causal Inference, NLP, and Computer Vision to provide insights and automate workflows for advertisers.

This role focuses on developing and deploying 1P audience segments for Amazon's EU marketing campaigns, using causal inference and machine learning to measure incremental lift and optimize marketing spend. The goal is to move beyond platform-led optimization to more personalized customer experiences, building reusable frameworks for scalable experimentation and informing future marketing strategies.