Amazon

Senior Applied Scientist role focused on building AI-powered tooling for AWS Security operations, including generative AI incident response assistants, natural language-driven response, detection enrichment pipelines, and security data analytics platforms. The role involves defining and executing the ML/AI roadmap, extending and inventing techniques at the product level, and bringing models from research into production systems. Responsibilities include LLM-powered incident triage, anomaly detection, RAG, prompt engineering, fine-tuning, developing evaluation frameworks, and mentoring engineers.

Applied Scientist at AWS Marketplace focused on building and improving AI/ML-powered discovery systems. The role involves developing models for search ranking, query understanding, and recommendations, and extending these into agentic discovery experiences using multi-agent systems. Collaboration with engineers and product managers to deploy solutions into production is key.

Software Development Engineer II role on the Same Day Delivery Experience team, focusing on building and scaling AI-powered tools using LLMs, RAG, NLP, prompt engineering, and agentic AI workflows to enhance customer experience and protection. Responsibilities include designing and building AI tools, developing retrieval pipelines, prototyping agentic AI capabilities, and working on scalable AI/ML systems.

This role focuses on managing AI-focused customer engagements end-to-end, partnering with engineers and designers to deliver AI solutions using technologies like LLMs, RAG, and autonomous agents. The role involves orchestrating customer engagements, facilitating solution design, identifying opportunities, building relationships, and ensuring responsible AI practices.

Sr. Applied AI Solutions Architect focused on accelerating customer adoption of Amazon Connect's AI capabilities. The role involves guiding customers in model selection (via Amazon Bedrock), prompt configuration for AI agents, and architecting tool integrations (APIs, Lambda, etc.) for agentic AI systems. A key aspect is ensuring customer data readiness for AI agents and RAG. The role is hands-on, requiring coding, building integrations, and configuring agents, working at the intersection of contact center operations and applied AI.

Senior Software Development Engineer to lead AI/ML/LLM/VLM/VLA development for automating manufacturing engineering workflows, including agentic AI, robotic control, and computer vision for quality assurance.

Research and develop generative AI technology for Amazon Connect, focusing on LLM Agents and their evaluation/optimization to disrupt customer service experiences. The role involves building ML models from conception to deployment, prototyping, and iterating on state-of-the-art Agentic AI systems.

This role manages a team of applied scientists and engineers focused on developing ML and RL algorithms for robotic systems to optimize stow strategy and warehouse capacity. It involves leading research, design, deployment, and evaluation of these systems, with a focus on transformer architectures, affordance learning, and geometric reasoning in high-density environments.

Seeking an Applied Scientist with expertise in AI, Agentic LLMs, Generative AI, Machine Learning, and NLP to build LLM-powered solutions for Amazon's BuyForMe product. The role involves developing agentic frameworks, LLM fine-tuning, reinforcement learning, prompt engineering, RAG, MCP, and automated benchmarking to improve shopping workflows.

Senior Applied AI Solutions Architect for Federal Financial Regulatory customers, focusing on designing and enabling AI/ML solutions for fraud detection, market surveillance, regulatory reporting, and consumer protection. The role involves technical guidance, developing reference architectures, and enabling customer adoption of AI/ML on AWS, with a strong emphasis on agentic systems and RAG.

Manager for the Amazon Sponsored Agent (ASA) team, focusing on building and scaling a new agentic service for conversational and agentic ads. The role involves leading a team to develop a multi-agent system architecture for contextual ad serving, conversation understanding, and commercial insights generation, with a focus on AI-native ad formats.

This role leads the science function in WW Stores Finance, driving AI/ML innovations in financial analytics. The leader builds and directs a multidisciplinary team to deliver scalable solutions, translating AI capabilities into production systems. The role requires strategic vision and execution excellence to transform finance operations, automate workflows, and improve forecasting and controllership through agentic AI, ML, and generative AI.

Senior Applied Scientist role at Amazon's FinTech organization, focusing on building and scaling generative AI applications and autonomous agents for financial operations. The role involves developing systems that process financial transactions, extract intelligence from documents, and power agents that learn from customer interactions. Key responsibilities include ensuring AI systems are trusted for compliance, designing agents that improve with user feedback, optimizing inference at scale using tiered models and LLMs, and developing robust evaluation frameworks. The position emphasizes shipping production-ready models, working across the full stack, and solving complex real-world financial problems.

This role focuses on designing and implementing innovative AI solutions, developing ML models and frameworks, enabling self-service automation, and building evaluation frameworks to enhance productivity and unlock new value within Audible. The role involves applying ML/AI approaches to solve complex real-world problems and building the blueprint for how Audible works with AI.

Senior Applied Scientist role focused on improving advertising performance and delivering innovative advertising experiences for Amazon devices and grocery. The role involves building and deploying machine learning models, with a specific emphasis on agentic AI for ads targeting, including autonomous agents, multi-agent orchestration, large multimodal models, reinforcement learning, and sequential decision making. The position requires experience in developing scalable data pipelines, optimizing conversion KPIs, and staying updated with the latest advancements in ML, NLP, and multimodal learning.

Machine Learning Engineer role focused on designing, implementing, and scaling AI/ML solutions for AWS customers. This involves selecting, fine-tuning, and deploying models, identifying use cases, and providing technical guidance on responsible AI adoption. The role requires experience with ML/statistical modeling, software engineering best practices, and a Top Secret security clearance.

Machine Learning Engineer on AWS Professional Services team, focusing on designing, implementing, and scaling Generative AI solutions for customers. Requires TS/SCI clearance.

Applied Scientist II role focused on building AI-based automated customer service solutions using RAG, agentic AI, and post-training of LLMs. Responsibilities include designing and deploying RAG pipelines, conducting LLM post-training, curating datasets, implementing evaluation frameworks, developing AI agents, and collaborating with cross-functional teams. The role involves research and development with minimal guidance, aiming to translate research into production systems and contribute to the scientific community.

This role focuses on accelerating customer adoption of Amazon Connect's AI capabilities by acting as an Applied AI Solutions Architect. The architect will guide customers in selecting foundation models, designing and optimizing AI prompts, and architecting tool integrations for agentic AI systems. A key aspect is ensuring customer data readiness for AI agents and helping customers move from proof-of-concept to pre-production for Amazon Connect + Unlimited AI deployments. The role involves hands-on coding, building integrations, configuring agents, and collaborating with customer engineering teams.

Senior Machine Learning Engineer at AWS Identity Analytics Platform, focusing on building an AI-driven analytics platform that processes petabyte-scale data to generate insights for security and operational problems. The role involves designing, developing, and deploying ML solutions, including anomaly detection, time-series forecasting, classification, optimization models, and LLM-powered agents for conversational data querying. It also includes feature engineering, production deployment, and collaboration with leadership and service teams.

Senior Applied AI Solutions Architect for Amazon Connect, focused on accelerating customer adoption of AI capabilities. The role involves guiding customers in model selection, prompt configuration, and tool integration for AI agents, with a strong emphasis on customer data readiness and enabling multi-agent orchestration. This is a hands-on role requiring coding, integration building, and pair-programming with customer teams to move from proof-of-concept to production.

Senior AI Architect role focused on designing and building AI agents for AWS Professional Services to automate and accelerate consulting services delivery. The role involves working with customers, leading technical solutions, and architecting scalable AI/ML and GenAI solutions on AWS.

Product Manager for an AI-powered infrastructure reliability platform that uses LLMs and multi-agent systems to prevent, detect, and resolve incidents in Amazon's fulfillment network. The role involves defining product roadmaps, writing code for proof-of-concepts, and collaborating with data scientists and engineers on ML model applications, agent architecture, and evaluation frameworks.

Software Development Manager to lead a team building agentic AI systems for AWS Glue, EMR, and Athena, focusing on automated Spark upgrade and migration agents, and a managed analytics service providing AI assistants and agents access to tools. The role involves owning design, implementation, testing, and deployment, driving technical decisions at the intersection of GenAI, distributed systems, big data, and ML, and partnering with senior leadership and customers.

This role is for a Principal GenAI Specialist SA at Amazon, focusing on designing and architecting scalable, secure, and cost-effective AI/ML, Generative AI, and Agentic AI solutions on AWS. The role involves guiding customers through their AI transformation, establishing GenAIOps practices, and creating enterprise-grade AI architectures. It requires deep technical experience across the AI spectrum, including LLM customization/fine-tuning, inference optimization, agentic frameworks, GenAIOps, security, RAG systems, and prompt engineering.

Applied Scientist role focused on developing and deploying production-ready AI/ML models for consumer-facing features like content understanding, recommendations, and GenAI applications. The role involves inventing new approaches, adapting existing ones, and building scalable, efficient solutions. It requires collaboration with scientists and engineers, with a focus on both scientific and engineering best practices, and potentially contributing to research papers. The role touches on inference infrastructure and model serving, with a primary focus on building agentic or product-level AI features.

The Applied Scientist II will focus on building industry-leading Conversational AI Systems using Generative AI, LLMs, NLU, 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. The team explores new technologies and finds creative solutions for AWS customers, working with foundation models and generative AI to reimagine customer experiences.

Senior Applied Scientist role focused on building agentic AI products for businesses, involving end-to-end GenAI project ownership, ML model development and deployment, and research into innovative ML approaches. The role emphasizes building multi-agent systems using techniques like fine-tuning and reinforcement learning, with a focus on customer-facing features and scalable solutions.

This role focuses on researching and developing advanced navigation systems for intelligent robotic products, utilizing a spectrum of approaches from classical methods to learning-based techniques and foundation models. The primary goal is to enable robots to move reliably and safely in complex, dynamic environments, with a strong emphasis on sim-to-real transfer and evaluation frameworks.

Machine Learning Scientist role focused on Generative AI within AWS, aiming to identify customer needs and improve cloud adoption. The role involves building Agentic AI systems, fine-tuning LLMs, applying Reinforcement Learning, and generating insights from large datasets, with a focus on taking ideas from conception to production.

Solutions Architect for AWS Telco customers, focusing on customer experience transformation using AI agents, conversational AI, and omnichannel orchestration. The role involves designing and building solutions with AWS services like Amazon Connect and Bedrock AgentCore, driving adoption, and influencing product roadmaps.

Data Scientist to build and launch production-grade agentic capabilities for Amazon Seller Assistant, a multi-agent GenAI system. Responsibilities include analyzing seller pain points, designing measurement frameworks, applying NLP and statistical modeling, and collaborating with cross-functional teams to improve the seller experience at Amazon's scale.

Applied Scientist role focused on building LLM-driven conversational assistants for enterprise use cases in hospitality and senior living, leveraging Amazon's scale and data. Responsibilities include developing core LLM technologies, prompt optimization, and building/measuring metrics for these systems.

Senior Applied Scientist role focused on AI-driven structured field robotics, including path planning, fleet coordination, and control systems. The role involves leading research, translating breakthroughs into production solutions at scale, and owning end-to-end delivery of algorithmic solutions. It requires a PhD or Master's with significant experience in robotics, ML, and algorithm development, with a focus on publishing research and mentoring junior scientists. The team operates at the intersection of planning, algorithmic, and ML research with production systems.

Software Development Engineer role focused on building and launching production-grade, multi-agent GenAI systems for Amazon Seller Assistant. The role involves end-to-end ownership from customer insight to shipped product, operating at Amazon's scale.

The Applied Scientist II role focuses on developing and improving machine learning systems for industrial robotics, specifically leveraging and adapting foundation models for tasks like perception, reasoning, and action. This involves fine-tuning, optimization, experimentation, and building evaluation frameworks, with a contribution to data and training workflows. The goal is to enable generalization, multi-modal learning, and skill acquisition in robots operating at Amazon's scale.

This role focuses on developing advanced machine learning approaches and agentic systems for trust and safety in AWS cloud communication services. The primary goal is to create behavioral detection models and intelligent resource allocation algorithms that adapt to evolving threats and optimize service delivery. The role involves researching novel AI agent applications in security, integrating science components into production, and conducting rigorous experimentation.

Director of Software Development for Alexa Connections, leading a team to build communication experiences and AI primitives using generative AI, LLMs, voice, and GUI. Focuses on customer-facing UX, communication systems, third-party interfaces, and LLM architecture optimization for Alexa+.

Data Scientist to build and launch production-grade agentic capabilities for Amazon Seller Assistant, a multi-agent GenAI system. Responsibilities include analyzing seller pain points, designing measurement frameworks, applying NLP and statistical modeling, and collaborating with cross-functional teams to improve the seller experience at Amazon's scale.

Applied Scientist role at Amazon Advertising focused on building LLM-based solutions for advertiser support, predicting problems, and coaching users. The role involves applying NLP techniques, developing scalable ML solutions, and working with AWS services to create customer-facing applications.

Principal Applied Scientist at AWS Marketplace & Partner Services focused on developing and evaluating next-generation search, recommendation, and agentic systems to drive AWS revenue growth. The role involves defining technical strategy, leading innovations in information retrieval, recommendation systems, LLMs, and agentic AI, and mentoring other scientists. Key responsibilities include architecting agentic AI systems, bridging theory with practice, and contributing to the scientific community.

Senior Applied Scientist role focused on building machine learning and GenAI solutions, specifically agentic frameworks, to improve customer support for Amazon's selling partners. The role involves end-to-end development, collaboration with engineers and product owners, and applying state-of-the-art ML/GenAI techniques to automate workflows and diagnose issues.

Senior Software Engineer to lead technical vision and innovation for a new team building a horizontal agentic AI layer for Amazon Advertising. The role involves architecting and implementing robust systems using LLMs and autonomous agents to transform advertiser interactions with the platform.

Senior leader to build and lead a team of ProServe Cloud Architects specializing in AI, GenAI, and Agentic AI within the Healthcare and Life Sciences domain. The role involves counseling executives on AI transformation programs, developing repeatable partnership models, and designing scalable AI solutions. Requires expertise in AI/GenAI/Agentic AI within HCLS and experience in business development or professional services.

Senior Software Development Engineer role focused on leading the development and implementation of a generative marketing agentic framework (GeMA) at Amazon. The role involves designing a multi-agent architecture, establishing evaluation frameworks, and integrating AI-based solutions for personalized marketing at scale. It requires technical leadership, collaboration with cross-functional teams, and research into LLMs and multi-agent AI systems.

Product Manager - Technical role for an AGI Autonomy Lab focused on developing foundational capabilities for AI agents. The role involves defining and prioritizing tooling roadmaps for data collection, model evaluation, and release processes, bridging research and engineering by translating technical needs into product requirements. Key focus areas include combining LLMs with RL for reasoning, planning, learned world models, and generalizing agents to physical environments.

This role focuses on developing advanced robotics systems that integrate AI, control systems, and mechanical design for automation. The scientist will lead the design and implementation of methods for Visual SLAM, navigation, and spatial reasoning, leveraging simulation and real-world data for model development. The goal is to create a hierarchical system combining low-level control with high-level planning for dexterous manipulation and human-robot interaction.

Software Development Engineer III at Amazon Annapurna Labs, focused on building AI agents and tools to simplify and accelerate customer adoption of AWS Neuron, the software stack for Amazon's ML silicon (Trainium). The role involves technical leadership, research, and delivery of innovative software solutions to improve ML workload porting and optimization on AWS hardware.