Applied Scientist role at Amazon Prime Video focusing on Playback Intelligence. The role involves using applied machine learning and data science, with specializations in video streaming optimization, information retrieval, anomaly detection, root-causing systems, large language models, and generative AI across various modalities. Responsibilities include translating business requirements into deliverables, improving customer playback quality, reducing time/cost/effort for optimization and defect mitigation, and integrating new algorithms into modeling stacks. The role emphasizes working backwards from desired outcomes to determine ideal solutions.

Senior Software Development Engineer to drive the technical direction of the Catalog & Events services within the Workshop Studio platform, focusing on building AI-powered agentic systems for content discovery, participant guidance, automated summaries, and agent-assisted authoring. The role also involves developing multi-tenant platform infrastructure, integration APIs, and evolving the authentication architecture, with a strong emphasis on technical leadership and operational excellence.

Applied Scientist role focused on building and delivering state-of-the-art science and engineering solutions for Amazon's Stores business, leveraging machine learning, optimization, and economics to improve business metrics. The role involves developing and maintaining scientific models, benchmarks, and services, and deploying solutions in partnership with product teams.

Machine Learning Engineer to build and deploy agentic AI products within AWS Applied AI Solutions. The role involves transforming research into production systems, owning end-to-end deployment, and establishing scalable ML processes.

Solutions Architect role focused on driving adoption of AWS cloud solutions for Consumer Packaged Goods (CPG) companies, with a specific emphasis on Generative AI and Agentic AI. The role involves understanding CPG business challenges, architecting cloud solutions, educating customers on AWS capabilities, and helping them navigate the shift towards AI-driven operations and autonomous agents. This includes driving adoption of GenAI for demand forecasting, agentic ERP exception handling, and supply chain analytics, as well as building relationships with stakeholders and advocating for CPG-specific product needs.

Software Development Engineer II, Post Silicon Validation for AWS's next-generation machine learning accelerators. This role involves validating the complete vertical stack of ML accelerators, from silicon to system, ensuring quality and performance for AWS cloud infrastructure. Responsibilities include developing validation strategies, executing test plans, hardware bring-up and debug, and collaborating with cross-functional teams.

Software Development Engineer III for Amazon's Sponsored Products and Brands team, focusing on building conversational ad experiences powered by LLMs. The role involves developing large-scale, low-latency distributed systems, ML infrastructure, LLM-based AI workflows, and contributing to LLMOps, with a focus on customer-facing functionality impacting millions of shoppers.

This role focuses on building and presenting generative AI demonstrations for AWS customers, educating them on AI technologies and providing architectural guidance for solutions involving AWS services and partner offerings. The role involves creating industry-grade demos, delivering compelling tours, and facilitating hands-on experiences to drive customer engagement and pipeline opportunities.

Applied Scientist role focused on developing and productizing AI solutions for enterprise services within AWS. The role involves designing and implementing ML systems for diverse applications, creating scalable algorithms, conducting experimentation with advanced techniques (LLMs, CV, agentic AI), and collaborating with engineering and product teams to deliver customer impact. The primary output is shipped AI products, with a secondary focus on agentic AI systems.

Principal Solutions Developer role focused on building prototypes and customer engineering solutions using AI, Agentic Design, Serverless, and multimodal Generative AI. The role involves partnering with customers to explore new technical grounds, craft scalable solutions, and accelerate AWS adoption. It requires a builder's mentality, technical depth, business acumen, and the ability to operate independently in ambiguous environments.

This role focuses on building and operating AWS cloud infrastructure for AI training and inference, specifically targeting high-performance and scalable solutions for large language models. The engineer will work on server designs, system-level debugging, and implementing automation solutions, including agentic workflows and AI-driven tools, to enhance the productivity of other engineers and influence AI implementation and core architecture.

This role focuses on building and presenting generative AI demonstrations for AWS customers, educating them on AI technologies and providing architectural guidance for solutions involving AWS services and partner offerings. The role involves creating industry-grade demos, delivering compelling tours, and facilitating hands-on experiences to drive customer engagement and pipeline opportunities.

The Applied Scientist II role on the Amazon Search team focuses on inventing signals and algorithms for machine-learned ranking models to improve search quality for millions of customers. The role spans the entire development pipeline, from data analysis and prototyping to A/B testing and production deployment.

Applied Scientist role focused on developing Agentic AI solutions using Gen AI within AWS Applied AI Solutions. The role involves extending scientific techniques, inventing new ones, and delivering components into production with high quality standards. Requires experience in building models for business applications and strong programming skills.

Backend engineer responsible for building and operating core services that ingest, process, and distribute large-scale, multi-modal datasets to internal tools and data pipelines for an AGI research lab. Focuses on designing backend architecture, defining operational standards, and ensuring production health, performance, and observability.

Software Engineer on the Research Tools Platform team at Amazon AGI Autonomy, responsible for building tools that support model development, data creation, evaluation, and experimentation for AI agents. The role involves defining system architecture, building UI components, and collaborating with researchers and engineers.

Data Scientist II at Audible (Amazon) focused on building production-ready LLM solutions and recommendation systems. Requires a Master's degree and 2+ years of experience in data science, ML modeling, Python/R, and non-linear models. Experience with LLMs (programmatic access, evaluation, fine-tuning), recommendation systems, and SQL/ETL is required.

Senior Software Development Engineer role focused on building and owning the design and delivery of critical infrastructure components for AI agents in Amazon Ads. This includes an agent-builder SDK, agent-builder tools, and a managed runtime, enabling advertisers to build and deploy AI agents at scale. The role involves working at the intersection of distributed systems, ML infrastructure, and developer tooling, defining technical strategy for scalable platforms in an emerging space.

This role focuses on developing and customizing ECAD applications, with a significant emphasis on integrating AI/ML technologies to enhance design processes. The engineer will lead the customization and extension of Cadence applications, explore AI-based design review and generation capabilities, and collaborate with AI/ML teams to integrate LLMs and ML into ECAD workflows. The goal is to enable intelligent automation and design assistance in hardware engineering.

Senior Software Development Engineer role focused on building innovative solutions for brand measurement in Amazon Ads, leveraging generative AI and machine learning to optimize advertising performance and deliver AI-driven insights to advertisers.

This role focuses on designing and developing large-scale agentic AI systems for Alexa's communication features, aiming to redefine intelligent conversational experiences. The engineer will lead the development and scaling of real-time agentic AI solutions, collaborate with cross-functional teams, and ensure high quality and customer experience.

Senior Data Scientist role at AWS ProServe focused on designing, implementing, and scaling AI/ML and Generative AI solutions for enterprise customers. The role involves working directly with clients to understand their needs, develop statistical models, select and train models, and guide them through their AI transformation journey. Requires strong expertise in data science, ML, generative AI, and AWS cloud services, with a focus on delivering customer success and business value through AI.

Senior Applied Scientist role focused on designing and evaluating algorithms for predictive modeling and optimization in large-scale transportation planning systems. This involves developing novel machine learning and AI techniques to improve marketplace optimization solutions, working closely with business leaders and engineers to build scalable products, and implementing models within production systems.

Applied Scientist II at Amazon Fulfillment Technology (AFT) Science, focusing on developing production solutions for Amazon's Fulfillment Network using operations research, optimization, statistics, machine learning, and GenAI/LLM. The role involves designing, building, and deploying scalable mathematical models and optimization-driven solutions to improve process efficiency and associate experience within the fulfillment network. Collaboration with scientists, software engineers, and product managers is key, with a focus on translating research into production systems.

Senior Manager role focused on leading AI/ML innovation for network planning solutions, involving demand forecasting and network optimization algorithms. The role requires developing and deploying production-ready models, architecting scalable AI/ML infrastructure, and driving scientific innovation from research to production, ultimately translating AI/ML capabilities into measurable business outcomes. It emphasizes leading a team of applied scientists and collaborating with cross-functional partners.

Machine Learning Engineer II on an Amazon Special Projects team focused on creating new products and services using Generative AI and LLMs. Responsibilities include developing and maintaining platforms for LLM development, evaluation, and deployment, processing large datasets, scaling models, and optimizing performance. Experience with distributed model training is required.

Senior Software Engineer role focused on architecting and building next-generation robotic systems for warehouse automation. The role involves designing motion planning algorithms, developing vision-guided manipulation systems, and orchestrating complex multi-step workflows using behavior trees or state machines. Experience with robotics middleware (ROS/ROS2) and ML frameworks is preferred.

This role focuses on enabling Private Equity (PE) firms and their portfolio companies to leverage Generative AI and Machine Learning to solve business challenges. The Solutions Architect will design and architect end-to-end AI/ML solutions, including AI agents and RAG applications, using AWS AI services. The role involves partnering with PE firms, understanding business requirements, and guiding customers in architecting enterprise-grade GenAI solutions.

Senior Applied Scientist role focused on using ML/AI to understand demand-side signals in e-commerce, empower sellers to grow their business, and improve customer experience. Responsibilities include developing scalable seller-facing solutions, analyzing business data, designing and evaluating innovative models, and collaborating with engineering teams for real-time implementation.

Applied Scientist role at Amazon Ads focusing on Generative AI, AI Agents, and large-scale ML for demand forecasting. Responsibilities include leading ML initiatives, developing and optimizing forecasting models, building and deploying ML models, designing A/B experiments, establishing scalable ML infrastructure, and researching innovative ML techniques. Requires 3+ years of model building experience, a PhD or Master's with 4+ years of experience in a related field, and programming experience in Java, C++, or Python. Preferred qualifications include experience with experimental design and deep learning frameworks.

The role focuses on applying advanced analytical, statistical, and machine learning techniques to improve Amazon's Selling Partner experience through a Generative AI-powered conversational assistant. Responsibilities include analyzing seller pain points, evaluating feature performance, designing measurement frameworks (A/B testing, causal inference), applying NLP and statistical modeling to unstructured data, and partnering with cross-functional teams to influence product roadmaps. The goal is to enhance the Selling Assistant by responding to seller feedback and implementing fixes in the GenAI solution.

The Sr. Applied Scientist Pricing Optimization role at Amazon Leo focuses on building foundational ML models to optimize pricing and product feature strategies for a satellite broadband network. This involves predicting customer behavior, modeling multi-product bundling, and implementing scalable inference systems.

Software Engineer focused on performance optimization for distributed training of large-scale AI/ML models (LLMs, multi-modal) on AWS Neuron accelerators. This involves tuning across the software stack, including collective communications, memory utilization, compiler optimizations, and kernel performance, working with PyTorch and JAX.

Seeking a Software Engineering Manager to lead a team developing compiler optimization algorithms and deploying a new compiler for AWS custom hardware (Inferentia and Trainium chips). The role involves technical leadership, mentoring, and partnering with AWS ML services teams to improve deep learning model performance and productivity.

Software Development Engineer III role at Amazon, focused on building and optimizing the core components of the Amazon Quick Suite, an AI-powered assistant for enterprise productivity. The role involves leveraging generative AI to transform how businesses operate by answering questions, providing summaries, generating content, and completing tasks securely based on enterprise data, with a strong emphasis on unifying disparate data sources through secure connectors.

Software Development Engineer II at Amazon's Annapurna Labs, focusing on distributed AI/ML systems and collective operations for scaling AI across multiple accelerators and servers. The role requires strong C/C++ and Linux skills, with experience in embedded systems, high-speed networking, or HPC interconnects being valuable. This position is on the forefront of AI/ML, working with large-scale clusters and models within AWS's EC2 infrastructure.

This role focuses on providing domain expertise to human-in-the-loop and model-in-the-loop data pipelines for LLM training and evaluations. The Senior Domain Expert Lead will ensure data quality, optimize data collection, and mentor junior team members, while staying updated on GenAI applications in their domain.

Senior Applied Scientist role focused on developing next-generation advanced robotics systems that combine AI, control systems, and mechanical design for automation at Amazon's scale. The role involves research and implementation of deep learning and LLMs for robotics, with a focus on simulation, physics-based modeling, and sim-to-real gap reduction.

This role is for a Sr. Machine Learning Compiler Engineer III on the AWS Neuron team, focusing on the development and scaling of a compiler for ML accelerators. The role involves architecting and implementing features for a deep learning compiler stack that optimizes neural network performance on custom AWS hardware, integrating with frameworks like PyTorch and TensorFlow. The goal is to provide significant performance improvements for large-scale ML workloads.

Applied Scientist role focused on developing and implementing forecasting and optimization models using ML and GenAI to support real estate and store planning decisions for Amazon's grocery business. The role involves analyzing large datasets, building end-to-end solutions, and collaborating with cross-functional teams to drive adoption of insights and models.

This role focuses on building and deploying reliable, scalable, and high-performance ML/AI solutions, leveraging Big Data, AppDev, or DevOps experience. It involves working closely with Data Scientists and Data Engineers to deliver end-to-end solutions, utilizing ML frameworks, algorithms, and ML pipelines, with a strong emphasis on hosting and deployment of models.

Software Development Manager for AWS Neuron Tools team, responsible for leading engineers to develop and maintain high-performance monitoring and profiling tools for AI accelerators (Inferentia, Trainium). The role involves managing the full development lifecycle of the Neuron Profiler, ensuring scalability, reliability, and usability, and collaborating with cross-functional teams to optimize AI workloads. Experience with ML-specific profiler tools and performance analysis is required.

Senior Data Scientist role focused on developing and deploying machine learning models and AI agents for logistics optimization, fraud detection, and revenue management. The role involves end-to-end model development, from data analysis to production deployment and monitoring, with a focus on agentic AI systems and ML-powered fraud detection.

Data Scientist for Prime Air focusing on applied ML and experimentation to improve customer journey, drive expansion, and optimize delivery operations. The role involves developing statistical and ML techniques, building predictive models, designing experiments, and presenting findings to leadership, with a focus on shipping models that have a direct business impact.

The Language Engineer II role focuses on improving Alexa Shopping features by generating high-quality data, running experiments, and prompt engineering Large Language Models for API delivery. This involves analyzing and automating processes for collecting and annotating LLM inputs/outputs, applying Generative AI techniques, and optimizing data representation of human language. The role collaborates with scientists, engineers, and program managers to enhance the voice shopping experience and owns customer-facing ML models for specific features.

Senior Manager, Applied Science for Marketing Measurement and Performance Science (MAPS) at Amazon. This role focuses on building scalable ML and causal inference solutions to estimate marketing effectiveness and provide insights for marketing teams. It involves leading a team of scientists, developing end-to-end causal inference models, and influencing multi-billion dollar investment decisions. The role requires expertise in ML/DL, statistics, economics, and handling large datasets at scale, with a focus on delivering data-driven solutions that impact business strategy and customer behavior.

Senior Software Development Manager for Kiro, an intelligent development environment focused on Agentic AI systems. The role involves leading engineering teams to build innovative AI products from the ground up, partnering with ML science teams, and working at the intersection of AI and cloud services. The focus is on building foundational AI services and agentic systems for enterprise customers.

Manager for an Applied Science team focused on developing and deploying machine learning and optimization solutions for Amazon's publisher monetization platform. The role involves leading science and engineering teams, defining technical roadmaps, and collaborating with stakeholders to drive business impact at scale.