Amazon

This role focuses on guiding enterprise customers in adopting and scaling GenAI/ML and Agentic technologies on AWS. The Specialist Solutions Architect will act as a trusted advisor, designing technical architectures, providing recommendations on various aspects of cloud services, and influencing the roadmap of AWS GenAI/ML and Agentic features. The role involves creating and sharing best practices, technical content, and reference architectures, as well as evangelizing AWS technology through various channels.

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.

Software Development Engineer focused on building and scaling real-time agentic AI systems for Alexa's communication features, involving design, architecture, and full-stack development.

Software Development Engineer role focused on building agentic APIs and integrating advanced AI technologies (Generative, Agentic, Real-time AI) into Alexa's communication features. The role involves influencing product strategy, optimizing for low latency and scalability, and ensuring high-quality software delivery within an Agile environment.

Senior Software Development Engineer role focused on building agentic APIs and cloud services for Alexa Connections, leveraging Generative, Agentic, and Real-time AI to enhance conversational experiences. The role involves influencing product strategy, optimizing software for performance, and leading integration of AI systems.

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.

Manage a team of engineers building ML and generative AI systems for retail operations automation, focusing on catalog management, supply chain, and operational efficiency. The role involves architectural decisions, mentoring, and cross-team coordination to deliver scalable, reusable platforms.

The role is for a Senior Manager of Software Development focused on building next-generation Agentic security systems at Amazon. The position involves leading teams to create AI-powered security products from the ground up, working at the intersection of AI and security at a large scale. The manager will collaborate with security, engineering, and science leaders, and shape products that transform business security practices.

Applied Scientist role focused on building machine learning models for Amazon Search, developing new ranking features, and improving the ML framework for training and offline evaluation. The role involves designing, developing, and implementing production-level code for billions of search requests, with an emphasis on low-latency predictions and high throughput systems.

Software Development Engineer role focused on building and deploying computer vision and machine learning systems for Amazon's global fulfillment network. The role involves end-to-end ownership of systems that provide vision-based insights for item identification, defect detection, and decision-making in manual and robotic operations, supporting downstream business processes and flagship devices.

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.

AWS Solutions Architect role focused on prototyping with Agentic AI, Machine Learning, Deep Learning, Generative IA, IoT, and Serverless Architectures. The role involves architecting and developing solutions to demonstrate the art of the possible to customers, with a focus on rapid, time-boxed prototyping engagements.

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.

Applied Scientist role focused on building machine learning and optimization models for Amazon's large-scale transportation planning systems, including dynamic pricing and network planning. The role involves designing, building, and implementing scalable products and algorithms within production systems, with a focus on external freight and marketplace operations.

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.

Senior Delivery Consultant (GenAI FullStack SDE) at AWS Professional Services, focusing on building end-to-end Generative AI applications for enterprise customers. The role involves full-stack development, designing and implementing AI agent architectures, and leveraging AI-powered development tools. The primary focus is on delivering solutions using AWS services, with a secondary emphasis on the underlying inference infrastructure.

Data Scientist role focused on building AI/ML-powered procurement applications using machine learning, NLP, and predictive analytics. The role involves designing, developing, and deploying models and data pipelines, translating business requirements into data-driven solutions, and impacting daily operations for Amazon's global workforce.

Software Development Engineer role focused on building agentic APIs and integrating advanced AI technologies (Generative, Agentic, Real-time AI) into Alexa's communication features. The role involves influencing product strategy, optimizing for low latency and scalability, and ensuring high-quality software delivery within an Agile environment.

Software Development Engineer role focused on building agentic APIs and integrating advanced AI systems (Generative, Agentic, Real-time AI) into Alexa's communication features, aiming for low latency, high reliability, and scalability.

Software Development Engineer II on the AWS Elemental Inference team, focused on building and shipping production code for AI-driven video processing systems. The role involves translating research into scalable services, improving performance, and implementing MLOps best practices for AI-enhanced systems.

This role focuses on developing and deploying machine learning models for communication experiences within Alexa. Responsibilities include end-to-end model development, experimentation, and leveraging LLMs to build applications, aiming to improve customer engagement and product performance.

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.

Applied Scientist II role focused on enhancing book reading and discovery experiences at Amazon by building models and/or agentic systems. Responsibilities include research, design, implementation, and delivery of novel solutions, collaborating with cross-functional teams, and writing production-ready code. Requires experience in programming languages and SQL, with a preference for publications at top-tier conferences.

Applied Scientist role focused on using machine learning and statistical techniques to create and deploy advanced algorithmic systems for optimizing business operations and customer value within Amazon's consumer businesses. The role involves end-to-end ownership of business problems, from data analysis and model development to real-time implementation and scaling.

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.

Lead a team building and scaling AI-powered compliance automation solutions using ML and LLMs for document processing at Amazon scale. Focus on driving technical strategy, developing advanced systems, and managing engineering and science teams.

Software Development Engineer role focused on building and scaling foundational services for computer vision and AI capabilities within Amazon Photos. The role involves architecting and developing solutions for processing large volumes of photo and video data, optimizing ML model serving infrastructure, and collaborating with ML scientists to productionize models.

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.

This role focuses on accelerating customer adoption of AI/Agentic applications by helping them build and scale solutions using AWS services like Amazon Bedrock and Frontier Agents. The Principal DevAx Solutions Architect acts as a trusted advisor, guiding customers through the full AI development lifecycle and influencing AWS service roadmaps based on customer needs and market trends.

Software Development Engineer Intern role focused on building AI-powered features for the OpenSearch platform. Responsibilities include developing code, designing distributed systems, and applying AI/ML techniques to enhance search relevancy and performance. The role involves contributing to an agent framework for intelligent data analysis and optimizing user interactions, with a secondary focus on the underlying inference systems.

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 core cloud services for Amazon's Sidewalk network, with a significant emphasis on developing and integrating generative AI solutions to enhance operational efficiency, automate debugging, improve testing, and generate documentation. The role also involves building AI-powered support systems for device behavior analysis and triage, creating AI-assisted development tools, and designing AI-driven analytics for service health monitoring.

Principal Software Development Engineer to architect and drive technical strategy for regulatory compliance and product safety, leading AI-powered initiatives to automate compliance workflows at massive scale. The role involves leading Zero-Touch Compliance, Unified Content Processing Pipeline, and Compliance Assist (conversational AI agents).

Applied Scientist role focused on building and deploying machine learning models for Amazon's Product Search, with an emphasis on developing new ranking features, ensuring low-latency predictions, and scaling systems to handle billions of search requests. The role involves full development cycle ownership, from design and implementation to A/B testing and production deployment, leveraging academic research and contributing to the search experience in new and existing markets.

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.

Software Development Engineer II role focused on building AI-powered systems for compliance and safety in e-commerce, integrating generative AI with traditional software engineering. The role involves developing AI systems for product safety assessment, catalog management, and seller safety, requiring experience in AI model deployment and scalable architectures.

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.

Applied Scientist II on the Amazon Books team focused on enhancing reading and discovery experiences by building and delivering AI models or agentic systems. Responsibilities include research, design, implementation, and collaboration with engineering teams to productionize solutions. Requires experience in building models, programming, and a strong understanding of algorithms and data structures.

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.

The role involves designing and implementing machine learning models for recommendation systems to improve Amazon's talent acquisition processes. It focuses on building ML products that match job seekers with opportunities and recruiters with talent, operating at a global scale. The work involves representation learning, reinforcement learning, and probabilistic modeling, with an emphasis on fairness and explainability.